Generative Ai Applications

Generative Ai Applications Engineer Jobs

7 jobs found

Today

Senior Staff Machine Learning Engineer, Agentic Application

ServiceNow Mountain View, CA

Mountain View, CA

Today

$201k - $352k/yr Full time Senior Agentic Ai Agentic Systems

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Job Description

ServiceNow is seeking a Senior Staff Machine Learning Engineer to apply advanced Machine Learning, with an emphasis on Generative AI, to enterprise business automation. The role focuses on agentic AI experiences delivered through conversational and GUI product interactions across chat and web channels.

Role Overview

This position combines technical leadership with product execution. You will design and implement agentic AI capabilities for stakeholder and end-user features, work cross-functionally to define and validate deliverables, and help expand the product to additional customers, domains, and global markets. The work also includes advancing the underlying agentic AI framework through pattern identification and feedback.

Key Responsibilities

Partner closely with GAI conversational framework experts to understand current capabilities and best practices.
Design and implement stakeholder and end-user product features using Agentic AI and technical approaches that deliver measurable business value.
Collaborate with PM, UX, and GTM teams to scope, define, and validate product deliverables.
Expand the product’s reach to more customers, domains, and global markets while maintaining quality and extensible engineering implementation.
Identify patterns and incorporate user and stakeholder feedback to further evolve the Agentic AI framework.
Grow into a well-rounded product engineer focused on applying LLM technologies for impactful products and strategic influence.

Required Qualifications

Ability to tech lead other engineers and drive end-to-end project delivery; strong communications and soft skills.
BS degree or higher in computer science or a related field.
10+ years of professional experience in scalable system development.
Strong product sense and a passion for building scalable web or conversational UI products.
Excellent cross-functional collaboration skills.
Demonstrated eagerness to learn continuously and willingness to work outside comfort zones.

Education

BS or higher in computer science or a related field.

Compensation and Benefits

Base pay: USD 201,300 - 352,300 per year, plus equity (when applicable), variable/incentive compensation, and benefits.
Health plans, including flexible spending accounts.
401(k) Plan with company match.
ESPP.
Matching donations.
Flexible time away plan.
Family leave programs.
Competitive On Target Earnings (OTE) incentive compensation structure (for sales positions).

Work Location and Work Persona

Location: Mountain View, CA (onsite).
Work personas may be flexible, remote, or required in office depending on the nature of work and assigned work location.
ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Company Overview

Moveworks is the Agentic AI Assistant platform that empowers the entire workforce. In December 2025, Moveworks was acquired by ServiceNow, marking a milestone in building a single front door to work for all business systems.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration without regard to protected characteristics.
Applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.

Accommodations

If you require a reasonable accommodation to complete any part of the application process, or are unable to use the online application and need an alternative method to apply, contact globaltalentss@servicenow.com for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, ServiceNow may need to obtain export control approval from government authorities for certain individuals.
All employment is contingent upon ServiceNow obtaining any export license or other approval required by relevant export control authorities.

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1d ago

Applied AI Engineer II - Encore Program

Deloitte Hermitage, TN

Hermitage, TN

1d ago

$103k - $189k/yr Full time Backend Developer Agentic Ai Ai Engineer

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Job Description

Build high-visibility, end-to-end AI-powered products with Deloitte’s Encore Program in Hermitage, TN (onsite). This role emphasizes accountability for customer and business outcomes, cost-aware engineering, and technical leadership across the full product lifecycle, including applied GenAI and agentic capabilities delivered through full automation from discovery to production to operations.

What you’ll do

Drive a culture of accountability for customer and business outcomes, including the cost to achieve them.
Design and implement lean engineering solutions to solve complex problems with valuable outcomes, including ownership of inference, token, and cloud costs for what you build.
Act as a technical advocate for products by ensuring code integrity, feasibility, and alignment with business and customer goals.
Participate across the lifecycle: requirements analysis, component design, development, testing, integrations, and support.
Maintain accountability for code and design integrity, implementation fidelity to the architecture and tech stack, plus quality, data, and ongoing maintenance and operations.
Translate business and user needs, architectures, and UX/UI designs into technical specifications and code.
Create technical specifications and write high-quality, supportable, scalable code that meets or exceeds quality KPIs.
Use rapid, inexpensive experimentation to develop solutions that address customer needs.
Partner with customers and product teams before, during, and after delivery to help ensure the right solution ships at the right time.
Adopt an evidence-driven approach that favors action over extensive planning, navigating complexity and uncertainty with maintainable delivery.
Collaborate with empowered, cross-functional teams including product management, experience, and delivery, integrating diverse perspectives to balance feasibility, viability, usability, and value.
Contribute to and improve a modern AI and agentic SSDLC approach to enable daily deployments with full automation and quality checks across the SSDLC lifecycle.
Learn quickly and build domain knowledge relevant to the business or product, including coaching others through role-modeling.
Communicate complex technical concepts clearly, influence teams with evidence-backed trade-offs, and align technical work to business objectives.

Requirements

Bachelor’s degree in computer science, software engineering, data science, machine learning, or a related discipline (experience is the most relevant factor).
3+ years of experience with many of: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, and unit testing frameworks.
2+ years building AI/ML and agentic applications, including hands-on GenAI work with LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration.
2+ years cloud-native engineering experience using FaaS, PaaS, or micro-services on Azure, AWS, or GCP, including AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI, plus application-level infrastructure-as-code and cost-aware engineering with FinOps accountability.
Prior software engineering experience including Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentation, plus AI-augmented spec-driven development.
Experience with methodologies and tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (for example LangFuse, LangSmith, or equivalent multi-agent orchestration tools) to deliver high-quality products rapidly.
Ability to travel 10% on average.
Limited immigration sponsorship may be available.
Candidates must be located within a commutable distance to one of the select locations for this role.
Ability to work in the local office at least 3 days per week.

Team and culture

Deloitte’s US Technology Product Engineering has modernized product delivery with a scalable, cost-effective model focused on value and outcomes, using a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions across businesses, service lines, and internal operations, helping power Deloitte’s success with internal and go-to-market solutions delivered with excellence.

Location and compensation

Location: Hermitage, TN (onsite)

Salary range: USD 102,500 to USD 188,900 per year.

The wage range reflects a wide set of factors used to make compensation decisions. It is not typical for an individual to be hired at or near the top of the range; compensation depends on the facts and circumstances of each case.

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1d ago

AI Engineer

Transformativ, LLC McKinney, TX

McKinney, TX

1d ago

$75 - $100/hr Contract Agentic Ai AI Ai Engineer

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Job Description

Transformativ, LLC is seeking an AI Engineer to help design, build, and deploy agentic AI and multi-agent systems that support enterprise clients. This hybrid role in McKinney, TX centers on production-grade LLM solutions, orchestration, and practical integration with business platforms.

Location and Work Arrangement

Primary: Hybrid remote in McKinney, TX 75070
Additional: Dallas, TX (Preferred) | Remote considered for exceptional candidates
Job type: Contract
Work model: 1099 Independent Contractor with contract-to-hire opportunity

Role Summary

The AI Engineer will focus on agentic AI, large language models (LLMs), and multi-agent systems to build and deploy production-ready AI solutions for enterprise customers. The work includes architecting, implementing, and integrating AI workflows and applications using modern LLM and orchestration tools.

Responsibilities

Design and deploy production-ready Agentic AI and multi-agent systems
Build enterprise AI applications using Python and LLM platforms such as OpenAI, Anthropic, Google Gemini, Azure OpenAI, or similar services
Develop AI workflows with orchestration frameworks including LangGraph, CrewAI, AutoGen, MCP, or comparable tools
Integrate AI solutions with APIs, databases, Microsoft 365, ERP, CRM, and other enterprise systems
Collaborate with business leaders to translate operational challenges into AI solutions
Lead technical design discussions and mentor other engineers when appropriate
Evaluate emerging AI technologies and recommend practical approaches

Required Qualifications

Professional experience building production AI applications
Strong Python development skills
Hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, Azure OpenAI, etc.)
Experience with Agentic AI, autonomous agents, multi-agent systems, or AI orchestration
Experience integrating REST APIs, databases, and enterprise applications
Excellent communication and client-facing consulting skills
Ability to explain complex AI concepts to both technical and business audiences

Compensation

Pay: $75.00 - $100.00 per hour
Rate basis: Competitive hourly rate based on experience

Technologies

Work may involve Python, OpenAI, Anthropic, Google Gemini, Azure OpenAI, LangGraph, CrewAI, AutoGen, MCP, Semantic Kernel, REST APIs, Microsoft 365, ERP, CRM, Azure, AWS, and Google Cloud, along with LLMs, Generative AI, Agentic AI, Multi-Agent Systems, and AI automation.

About Transformativ, LLC

Transformativ is an AI-first consulting firm specializing in business transformation through Generative AI, Agentic AI, LLMs, intelligent automation, and autonomous multi-agent systems. The company partners with private equity firms and mid-market enterprises to redesign business processes, eliminate manual work, and deploy production-ready AI solutions that deliver measurable business value.

Preferred Experience

LangGraph, CrewAI, AutoGen, MCP, Semantic Kernel, or similar orchestration frameworks
Cloud platforms including Azure, AWS, or Google Cloud
Experience in healthcare, manufacturing, supply chain, finance, procurement, or private equity
AI governance, security, evaluation, and responsible AI practices
Technical leadership or consulting experience

Role Focus and Collaboration

This position is centered on building real-world AI systems that automate business processes using modern LLM capabilities, autonomous agents, and enterprise integrations. The AI Engineer works directly with executives and client teams to architect, build, and deploy AI solutions into production, supported by technical design leadership and collaboration.

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2d ago

AI Engineer

Hollstadt Consulting Minneapolis, MN 🇺🇸 Remote

Minneapolis, MN

2d ago

$105k - $140k/yr Full time AI Ai Engineer Ai Engineering

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Job Description

Hollstadt Consulting is building out its AI Center of Excellence and needs an AI/ML Engineer to support cross-functional teams with production-focused machine learning, AI, Generative AI, and agentic AI solutions. This role is centered on designing and delivering end-to-end capabilities, from pipeline development to testing and secure integration across enterprise environments. This position is remote in Minnesota, with local preference.

Key work includes building production AI/ML pipelines and GenAI or agent capabilities tailored to domain-specific needs. The role supports automation of complex document understanding and structured content extraction, while also establishing reliability measures such as LLM testing frameworks and regression suites for drift and prompt breakage.

Responsibilities

Collaborate across GenAI platforms and libraries, including AWS, Salesforce, Oracle, Snowflake, MS Copilot, and other 3rd party GenAI platforms.
Automate workflows to extract highly accurate structured outputs from complex, multimodal unstructured content using tools such as AWS Textract and Bedrock.
Design and build Model Context Protocol (MCP) hosts, clients, and servers.
Establish and apply frameworks for automated LLM testing.
Create regression test suites to detect drift and prompt breakage.
Integrate with internal and external web services using secure authentication and authorization mechanisms.
Adopt safe practices to protect against prompt injections and jailbreaks, aligning with enterprise security guidelines.
Design, develop, and deploy production-grade traditional ML models including regression, classification, clustering, and recommender systems.
Design, maintain, and optimize end-to-end AI/ML pipelines across data ingestion, training, evaluation, deployment, and monitoring on cloud infrastructure such as AWS (or equivalent).
Ensure AI/ML solutions are scalable, reliable, secure, and cost-effective in cloud environments.
Create reusable components, frameworks, and best practices to accelerate AI development.
Design and develop GenAI solutions using prompt engineering, Context Engineering, Retrieval-Augmented Generation (RAG), and custom pipelines.
Design and develop interoperable AI agents using MCP and/or Google A2A.
Partner with data scientists, architects, product managers, business stakeholders, and technical teams to align AI solutions with organizational goals.
Provide hands-on technical support and mentorship to technical teams across the enterprise.

Requirements

3+ years of experience designing and deploying ML/AI solutions in real-world environments.
Very strong Python skills.
Strong hands-on experience with LLM APIs (including OpenAI, Azure OpenAI, Gemini, Anthropic) using Python and Python-based frameworks.
Strong hands-on experience with prompt engineering, context construction, and grounding strategies.
Strong hands-on experience with RAG workflows, including extracting, chunking, and creating embeddings from unstructured documents from sources such as O365 (email, Word, Excel), PDFs, and webpages.
Comfort building MCP clients, servers, and hosts.
Expertise building REST APIs and integrating with internal and external APIs.
Hands-on experience with Intelligent Document Processing and/or OCR technologies on complex documents.
Knowledge of Google A2A.
Deep experience in AWS including Lambda, Bedrock, Step Functions, API Gateway, and IAM.
Strong experience with observability tools such as Dynatrace or similar GenAI observability tools.
Excellent GenAI foundations and concepts, including enterprise data privacy, AI governance, and observability.
Proficiency in Python and common ML/AI libraries such as TensorFlow, PyTorch, and scikit-learn.
Strong understanding of data engineering, SQL, and feature engineering.
Hands-on experience with cloud services including AWS SageMaker, Lambda, ECS, S3, and IAM.
Familiarity with containerization (Docker) and orchestration (e.g., Airflow, Kubeflow).
Working knowledge of version control and collaboration tools such as Git, Jira, and Confluence.
Bachelor’s degree in computer science, engineering, or a related field.
Knowledge of machine learning algorithms, deep learning frameworks, cloud AI technologies, GenAI technologies, and emerging agentic AI technologies.
Knowledge of cloud platforms (AWS, Azure, GCP) for scalable AI/ML development.
Knowledge of responsible AI principles including bias mitigation and ethical deployment.
Knowledge of ML Ops best practices including CI/CD for ML, model monitoring, and versioning.
Ability to build robust, scalable, and efficient AI/ML solutions in cloud-native environments.
Ability to translate ambiguous business problems into clear technical ML/AI tasks.
Ability to communicate complex ideas clearly to technical and non-technical stakeholders.
Ability to learn and adapt quickly to emerging AI technologies, techniques, and tools.

Technologies

AWS, SalesForce, Oracle, Snowflake, MS Copilot
AWS Textract, Bedrock, Model Context Protocol (MCP), Google A2A
OpenAI, Azure OpenAI, Gemini, Anthropic
REST APIs, Dynatrace
TensorFlow, PyTorch, scikit-learn
O365, PDFs, webpages
Intelligent Document Processing, OCR
AWS Lambda, AWS Step Functions, AWS API Gateway, AWS IAM, AWS Sagemaker, AWS ECS, AWS S3
Docker, Airflow, Kubeflow
Git, Jira, Confluence, CI/CD, ML Ops
Retrieval-Augmented Generation (RAG), prompt engineering, Context Engineering, grounding strategies, embeddings

Compensation & Logistics

Location: Minnesota (remote); local preferred but not required
Salary: USD 105,000 - 140,000 per year, plus 8% AIP eligibility
Start date: 9/28/2026

Benefits

Comprehensive Benefit Plan including medical, dental, vision, life insurance, short-term disability, long-term disability, paid sick leave, and retirement benefits
401(k) + Matching: match on the first 4% of contributions
Bonus opportunities including Longevity Award bonus and referral bonus
Professional development with on-demand training through a consultant portal, including upskilling in Artificial Intelligence (AI)
Ongoing support and networking through a Consultant Coach program

Preferred Qualifications

Master’s in a related technical field
Hands-on experience with agentic AI frameworks
Prior contributions to open-source AI/ML projects or published research
AI/ML certifications from cloud providers
Experience in highly regulated industries (e.g., healthcare, finance) a plus

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2d ago

AI Engineer

Wipro Limited Austin, TX

Austin, TX

2d ago

$60k - $135k/yr Full time Agentic Ai Ai Engineer Ai Engineering

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Job Description

Wipro Limited is seeking a Senior AI Engineer to lead AI-focused workflows across the System Development Life Cycle, combining hands-on GenAI development with production deployment experience in complex, financial-domain environments that support retirement security.

Role Overview

This position focuses on building intelligent systems and AI-enabled workflows that operate across implementation, testing, and operational support. The role requires practical use of GenAI coding assistants in day-to-day engineering workflows, with clear ownership for correctness and quality, and the ability to apply engineering judgment in validation.

Key Responsibilities

Lead AI-focused workflows across the System Development Life Cycle.
Build intelligent systems that directly impact millions of people’s retirement security.

Required Skills and Qualifications

Demonstrated exposure to, or hands-on experience with, GenAI coding assistants used across day-to-day engineering workflows in the SDLC (implementation, refactoring, unit testing, regression support, code reviews, scripting or automation, troubleshooting, and documentation), applying engineering judgment and validation.
Practical familiarity with tools such as GitHub Copilot or Claude Code.
Use AI assistance for common development tasks (code suggestions, test generation, review support, automation scripts, and troubleshooting) with clear ownership for correctness and quality.
Apply GenAI to reduce context switching and accelerate delivery across typical engineering workflows, including but not limited to new code creation.
Practical familiarity with GitHub Copilot and/or Claude Code in IDE or CLI-style workflows.
Working knowledge of agentic workflows, spec-driven development (translating low-level design artifacts such as class structures, API contracts, and data models into structured specs that guide AI-assisted implementation), and custom instructions and prompt engineering, including establishing team-level practices for effective AI-assisted development.
Bachelor’s degree in computer science, Software Engineering, or a related technical field, or equivalent practical experience.
Hands-on experience in software engineering delivering large-scale systems using Java, Spring framework, cloud development, and web services supporting high volume transactions in a highly available environment.
Hands-on experience with AI/ML implementation and production deployment.
Hands-on experience with containers and microservices in the cloud.
Hands-on experience with cloud deployment within a continuous integration and continuous delivery model (CI/CD).
Hands-on experience with Pivotal Cloud Foundry (PCF), or AWS or GCP.
Hands-on experience with databases including MongoDB, Aerospike, and/or PostgreSQL.
Experience in IT transformations and system modernization initiatives from legacy to distributed platforms (for example, Mainframe Cobol apps/DB2 to Java apps/SQL or MongoDB).
Hands-on experience with Large Language Models (e.g., GPT-5, Claude, Gemini, PaLM).
Understanding of broker-dealer capabilities and operations.
Excellent communication skills with proven ability to communicate and lead other engineers in a collaborative environment.
Collaborative mindset with a bias for action to engage with developers, architects, and adjacent teams.
AI ML Solution Architecting.

Technologies

GenAI coding assistants
GitHub Copilot, Claude Code
Agentic workflows
Java, Spring framework
Cloud development, Web Services
AI/ML
Containers, microservices
CI/CD
Pivotal Cloud Foundry (PCF)
AWS, GCP
MongoDB, Aerospike, PostgreSQL
Mainframe Cobol, DB2
Large Language Models (GPT-5, Claude, Gemini, PaLM)

Experience Level

Experience range: 5-8 years
Minimum experience: 5 years

Education

Bachelor’s degree in computer science, Software Engineering, or related technical field, or equivalent practical experience

Preferred Qualifications

Master’s degree in Information Technology, Computer Science, related degree, or related practical experience
Good knowledge of messaging technologies (Rabbit MQ, Kafka, or equivalent)
Experience in the Financial Services industry
Experience in Test Driven Development (TDD), QA Automation, and quality mindset and behaviors
Proficient in developing Visio diagrams, architectural and design documentation, functional and technical specifications, and automated test process
Willingness to learn all aspects of the tech stack and document work
Ability to research and document production and test environments along with architecture and design work
Knowledge of Agile methodology and experience in an Agile working environment
Experience with the Atlassian tool stack (JIRA and Confluence)

Domain Expertise

Understanding of broker-dealer capabilities and operations

Location and Work Setup

Austin, Texas (onsite)

Compensation

USD 60,000 - 135,000 per yearly

Benefits

Full range of medical and dental benefits options
Disability insurance
Paid time off (inclusive of sick leave)
Other paid and unpaid leave options

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2d ago

AI Engineer

LawPro.ai Virginia

Virginia

2d ago

Full time Ai Engineering Artificial Intelligence Engineering

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Job Description

LawPro.ai is building AI-powered data insights and analytics, and they’re hiring an AI Engineer in Virginia (onsite) to own the evaluation, selection, and continuous optimization of large language models and AI processes. This role blends AI research with production engineering, with end-to-end responsibility for model transitions, pipeline optimizations, monitoring, and documentation.

What you’ll deliver

Run a systematic, ongoing process to evaluate new and emerging LLMs on accuracy, relevancy, speed, and cost, continuously benchmarking against the specific tasks in the orchestration pipeline.
Design and operate rigorous Evals and build an internal EvalOps culture to measure output accuracy, relevance, faithfulness, and speed, with focused effort on reducing hallucinations in medical record summarization and legal document analysis.
Track provider changes across the LLM landscape to identify deprecation timelines, then execute full transitions by integrating replacement models into the production pipeline and updating for model behavior differences.
Improve LLM-based orchestration for document understanding, medical record summarization, case chronology generation, and drafting support by implementing code changes, deployments, and production validation from start to finish with a bias for surgical execution.
Communicate evaluation findings with product and GTM stakeholders, then lead the technical implementation directly to ensure frictionless handoffs between discovery, staging, and live production deployments.
Ship model changes into production by writing integration code, managing deployments, running validation tests, and ensuring clean rollouts.
Implement monitoring and observability for model performance, including benchmarking outputs and cost, detecting drift, and reporting continuously to management using micro-benchmarking to track token-level latency, output drift, and cost efficiency across pipeline components.
Maintain thorough documentation covering evaluation methodologies, model comparison results, transition decisions, and runbooks for the systems you own.

What you bring

5+ years of AI/ML engineering experience evaluating, fine-tuning, and deploying large language models in production, including building and deploying models to AWS or GCP infrastructure at scale.
Hands-on development and implementation of multiple RAG solutions.
Hands-on experience leveraging embedding models and vector databases.
Hands-on experience building agentic workflows and implementing practical EvalOps or Evals-as-a-Service architecture.
Deep familiarity with the LLM ecosystem, with ability to assess model capabilities, limitations, and fit using tradeoffs across routing, cost, quality, speed, and capability.
Proven experience designing evaluation frameworks for output quality measurement, including hallucination detection in high-stakes domains (legal, medical, or similar).
Strong software engineering foundation with production experience building LLM orchestration frameworks and multi-model pipelines.
Comfort working in a fast-paced, high-ambiguity environment with strong ownership, tight feedback loops, and a bias toward systematic process-building.
Excellent communication skills to translate complex evaluation findings into clear recommendations for engineering, product, and non-technical stakeholders.
Bonus: experience with unstructured medical or legal document processing, or background in classical ML (statistics, embeddings, retrieval-augmented generation).

Technology focus

AWS, GCP

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2d ago

Principal AI Engineer, Applications

Granicus Remote 🌍 Remote

Remote

2d ago

$165k - $205k/yr Full time Backend Developer Manager AI

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Job Description

Granicus is hiring a Principal AI Engineer, Applications to help turn AI data and agent capabilities into secure, scalable, production-ready applications and workflows. This role owns architecture and hands-on development across the application layer, partnering with platform and business teams to deliver dependable user-facing experiences.

What you’ll do

Architect, build, deploy, and operate full-stack internal AI applications that combine agents, trusted business data, workflow automation, and human decision-making.
Move AI prototypes and agent capabilities into durable, repeatable workflows that teams across the business can adopt, partnering with the AI Transformation & Strategic Operations team to translate process maps, user needs, business rules, and operating constraints into applications.
Collaborate with the Principal AI Engineer, Platform to integrate applications with Granicus systems including the lakehouse, canonical metric layer, trusted data services, reusable agents, and evaluation systems, including co-design of end-to-end system architecture and clear ownership boundaries between the data and agent platform and the app layer.
Own application-level authentication and authorization, working with Security, Legal, Business Systems, and Engineering to translate policies and risk requirements into enforceable application controls.
Build and maintain application and workflow integrations with enterprise systems and systems of record.
Instrument applications to measure adoption, engagement, workflow completion, cycle time, and other operational indicators, and connect product telemetry to business outcomes in partnership with the AI Transformation & Strategic Operations team.
Establish reusable application patterns, templates, components, APIs, and development practices to help Granicus deliver internal AI applications more quickly and consistently.
Take responsibility for Granicus information security by preserving the Confidentiality, Integrity, and Availability (CIA) of Granicus information assets in accordance with the company’s information security program.
Ensure data privacy for employees and customers, their data, and complete all required privacy training in a timely manner according to company policies.

Required qualifications

7+ years of software engineering experience, including ownership of production applications.
Experience architecting and building full-stack applications, backend services, and APIs.
Experience integrating applications with enterprise systems of record.
Experience implementing enterprise identity and authorization.
Demonstrated ability to set technical direction and operate engineering work end-to-end as a senior individual contributor.
Hands-on familiarity with LLMs, agents, or retrieval systems through production work, prototypes, or internal tools.
Track record of translating ambiguous business problems into usable technical solutions.
Bachelor’s degree in Computer Science, Engineering, or a related technical field.

Technologies you’ll work with

LLMs, agents, retrieval systems
APIs
Lakehouse, canonical metric layer, trusted data services
Reusable agents, evaluation systems
Identity and authorization

Location and compensation

Location: Remote
Salary: USD 165,000 - 205,000 per year

Benefits

Flexible Time Off
Company-Wide Wellbeing Days
Work From Home Reimbursement
Multiple Health Plan Options (including a 100% employer-paid plan)
Employer HSA Contributions
Fitness Reimbursement Program
On-Demand Mental Health Support (Access to Headspace and other wellness tools)
Paid Parental Leave (for both birthing and non-birthing parents)
Traditional & Roth 401(k) (with a generous company match)
Life & AD&D Insurance (100% employer-paid coverage)
Online Learning Platforms
Competitive Salary & Bonuses

Team and culture

Remote-first company with a globally distributed workforce across the United States, Canada, United Kingdom, India, Armenia, Australia, and New Zealand.
Focus on building a transparent, inclusive, and safe space, including Employee Resource Groups.
“Coffee with Mark” sessions to interact with the CEO on topics that include mental health, work-life balance, and current affairs.
Microsoft Teams communities focused on wellness, art, furbabies, family, parenting, and more.
Special guests join from time to time to discuss issues that impact the employee population.

Equal opportunity employer

Granicus is committed to providing equal employment opportunities. All qualified applicants and employees will be considered for employment and advancement without regard to protected characteristics, including race, color, religion, creed, national origin, ancestry, sex, gender, gender identity, gender expression, disability, age, genetic information, sexual orientation, marital status, status with regard to public assistance, familial status, military or veteran status, and any other status protected by law.

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