Agents

Agents Engineer Jobs

5 jobs found

15d ago

Applied AI Engineer (Full-Stack)

Pinecone United States

United States

15d ago

$190k - $270k/yr Full time Backend Developer Agents Api Development

Apply Now

Job Description

Applied AI Engineer (Full-Stack) at Pinecone (United States, onsite) blends full-stack development with practical AI engineering. You will build and ship end-to-end LLM-powered applications that use retrieval and knowledge infrastructure, helping deliver AI experiences that are accurate, fast, and cost-effective.

What Pinecone offers

Comprehensive health coverage including medical, dental, vision, and mental health resources
401(k) Plan
Equity award
Flexible time off
Paid parental leave
Annual Company Retreat
WFH Equipment Stipend
Benefits and eligibility may vary by country of employment

Compensation Range: $190K - $270K

Responsibilities

Design, build, and ship end-to-end AI applications using Pinecone’s retrieval and knowledge infrastructure
Develop full-stack solutions across frontend interfaces, backend services, APIs, data pipelines, and LLM integration
Create reference applications, integrations, and reusable components to help developers and customers adopt Pinecone
Experiment with emerging AI patterns such as RAG, agents, tool use, context engineering, and agent memory
Partner with customers, partners, and internal teams to translate real-world problems into working software
Improve quality, reliability, latency, and cost of AI-powered applications
Share technical insights and best practices through code, examples, and technical content
Bring learnings back into Pinecone’s product and engineering teams

What you’ll need

Strong software engineering background with experience designing, building, and shipping production applications
Proficiency in Python and/or TypeScript, plus modern backend frameworks and frontend technologies such as React or Next.js
Experience building APIs, integrating external services, and working with databases and cloud infrastructure
Ability to take a project from rough requirements through implementation and deployment independently
Hands-on experience building applications using LLMs, embeddings, vector databases, or retrieval-augmented generation
Familiarity with modern AI development tools, frameworks, and APIs
Understanding of practical AI application challenges including retrieval quality, evaluation, latency, reliability, and cost
Curiosity about emerging patterns in agentic applications, context management, and AI-driven workflows
A builder mindset with comfort writing code, experimenting, and delivering working software
Comfort working with ambiguous requirements and making pragmatic technical decisions
Ability to communicate technical ideas clearly to engineers, customers, and stakeholders
Comfort moving from rapid prototypes to production-quality implementations
Interest in understanding how developers and customers use the technology and feeding that feedback into better solutions

Technologies you’ll work with

Pinecone, Python, TypeScript, React, Next.js, LLMs, embeddings, vector databases, retrieval-augmented generation, RAG, agents, tool use, context engineering, agent memory, APIs, databases, cloud infrastructure

About Pinecone

Pinecone is the trusted AI knowledge company. Its trusted AI knowledge platform, including its Database, Nexus, and Marketplace products, powers accurate, fast, and cost-effective AI applications for more than 10,000 customers and 1M developers worldwide. Pinecone’s mission is to make AI knowledgeable.

Bonus points

Experience with Pinecone or other vector databases and search technologies
Experience building agentic applications, agent memory systems, or complex RAG pipelines
Contributions to open-source projects, developer tools, or technical communities
Experience working directly with customers on technical projects
Experience deploying and operating AI applications in production

View full job page →

1mo ago

AI Engineer 4

Capital One New York, NY

New York, NY

1mo ago Closed

$215k - $246k/yr Full time Agents Ai Ml Artificial Intelligence

This position is no longer accepting applications (closed Nov 4, 2026).

Job Description

Capital One is hiring an AI Engineer 4 in New York, NY (onsite) to build and deploy responsible, scalable AI systems that support banking experiences for associates and customers. The role collaborates across engineering, research, program management, and product to deliver end-to-end AI architectures, performant model solutions, and reliable operations.

Responsibilities

Partner with cross-functional teams of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve how associates work and how customers interact with Capital One.
Design, develop, test, deploy, and support AI software components, including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Apply Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and related tooling.
Develop state-of-the-art foundation model optimization techniques to improve performance in production environments, including scalability, cost, latency, and throughput.
Help shape the technical vision and long-term roadmap for foundational AI systems.
Own end-to-end architecture for complex AI systems, focusing on maintainability, observability, and ethical alignment.
Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift.
Coordinate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are addressed.
Mentor Principal and Senior Associates on scalable system design, performance tuning, and research-to-production translation.

Requirements

Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields, plus at least 4 years of experience developing AI and ML algorithms or technologies; or a Master’s degree plus at least 2 years of experience developing AI and ML algorithms or technologies.
At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java.
At least 4 years of experience developing AI and ML algorithms or technologies.

Technologies

AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
Python, Go, Scala, CUDA, Java
Google Cloud, Azure, C++, C#, Golang
GPU/TPU

Preferred Qualifications

Experience leading development of AI systems with tradeoff decisions around cost, latency, throughput, and accuracy.
6+ years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
Experience designing, developing, delivering, and supporting AI services.
Experience developing AI and ML algorithms or technologies (e.g., LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang.
Experience building and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
Experience building agentic AI systems and agentic workflows.
Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale.
Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules.
Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.

Compensation

Salary: USD 215,200 - 245,600 per year.

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits designed to support your total well-being.

View full job page →

1mo ago

Staff AI Engineer

Capital One New York, NY 🇺🇸 Remote

New York, NY

1mo ago Closed

$245k - $279k/yr Full time Agents Ai Ml Artificial Intelligence

This position is no longer accepting applications (closed Nov 4, 2026).

Job Description

Capital One is hiring a Staff AI Engineer (remote eligible) to help build and deploy responsible, scalable enterprise AI systems across model training, inference, agents, evaluation, governance, and observability.

Responsibilities

Collaborate with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products used by associates and customers
Design, develop, test, deploy, and support AI components across foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
Apply open source and SaaS AI technologies including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and others
Introduce optimization techniques for large-scale production AI systems to improve scalability, cost, latency, and throughput
Shape technical vision and contribute to the long-term roadmap for foundational AI systems at Capital One
Set technical direction for enterprise-wide AI architecture, unifying tooling, observability, and deployment standards across teams
Own model routing, caching, and orchestration design and integration for hybrid and multi-model workloads
Advance responsible AI principles in system design, including transparency, reproducibility, and fairness-by-design
Support internal enablement through education, mentorship, and best-practice sharing via architecture councils and AI guilds

Requirements

Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 8+ years developing AI and ML algorithms or technologies
OR Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 6+ years developing AI and ML algorithms or technologies
8+ years programming with Python, Go, Scala, CUDA, or Java

Technologies

AWS Ultraclusters
Huggingface
VectorDBs
PyTorch
Python
Go
Scala
CUDA
Java

Team

The Intelligent Foundations and Experiences (IFX) team brings Capital One’s AI vision to life
Partners with teams across the company to advance science and AI engineering and to build and deploy proprietary solutions
Builds and deploys AI models and platforms that enable teams to enhance products with responsible, scalable AI at high leverage impact

Benefits

Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well-being

Ideal Candidate

Builds high-quality systems and shares a commitment to doing the right thing
Stays current with latest research and can understand scientific publications to apply techniques in production
Thrives in ambiguous, large-scale problems and can explain findings clearly
Works with strong engineering and mathematics fundamentals and can spot optimization opportunities across hardware, software, and AI
Demonstrates resilience and can forge new paths when the route is unknown

Preferred Qualifications

Experience designing AI systems with tradeoffs across cost, latency, throughput, and accuracy
8+ years deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud)
Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems
Ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to VP level
Experience developing AI and ML algorithms or technologies such as LLM inference, similarity search and VectorDBs, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang
Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost
Experience building agentic AI systems and agentic workflows
Excellent communication and presentation skills for articulating complex AI concepts
Track record defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability, and evaluation frameworks
Experience leading federated or multi-cloud AI strategies for resilience, compliance, and compute efficiency
Experience guiding model handoff, evaluation, and productization from research to production
Experience defining north-star metrics balancing business value, innovation velocity, cost, and ethical responsibility
Experience right-sizing models, instance counts, and hardware types based on requirements such as context length and token inputs/outputs

Compensation (Remote and Selected Locations)

Remote (regardless of location): $244,700 - $279,200
Cambridge, MA: $269,100 - $307,200
McLean, VA: $269,100 - $307,200
New York, NY: $293,600 - $335,100
San Francisco, CA: $293,600 - $335,100
San Jose, CA: $293,600 - $335,100

Notes

Capital One is open to hiring a Remote Employee for this opportunity
Capital One may consider sponsoring a new qualified applicant for employment authorization for this position
Applications are expected to be accepted for a minimum of 5 business days
No agencies please
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination
Capital One promotes a drug-free workplace
For technical support or questions about the recruiting process, email Careers@capitalone.com

View full job page →

1mo ago

Sr. Staff AI Engineer

Capital One McLean, VA

McLean, VA

1mo ago Closed

$315k - $359k/yr Full time Senior Agents Ai Engineer

This position is no longer accepting applications (closed Oct 24, 2026).

Job Description

Capital One is seeking a Senior Staff AI Engineer to design, build, deploy, and support AI software components and foundational AI systems. This onsite role in McLean focuses on foundation model training and inference, agent workflows, search, guardrails, evaluation, governance, observability, and long-term AI platform architecture.

Key Responsibilities

Collaborate with cross-functional teams of engineers, research scientists, technical program managers, and product managers to deliver AI-powered capabilities that improve how associates work and how customers interact with Capital One.
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Use a combination of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and other related tooling.
Develop state-of-the-art foundation model optimization techniques to improve production performance, including scalability, cost, latency, and throughput.
Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
Define and guide technical AI architecture, integrating applied research advancements into production environments that meet reliability and scale requirements.
Help establish AI performance, safety, and transparency standards that guide model development and deployment across the company.
Drive multi-year platform initiatives that unify data, compute, and model lifecycle management under a cohesive enterprise AI architecture.
Mentor senior technical leaders across research, data, and engineering groups to develop Capital One’s next generation of AI technical leadership.

Required Qualifications

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in a related field plus at least 8 years of experience developing AI and ML algorithms or technologies.
At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java.

Technology Focus

Programming: Python, Go, Scala, CUDA, Java
AI platforms and tooling: AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
Deployment ecosystem: Open Source, SaaS

Preferred Qualifications

Experience architecting AI platforms with tradeoff decisions across cost, latency, throughput, and accuracy.
9 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems.
Proven ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level.
Experience developing AI and ML algorithms or technologies (e.g., LLM inference, similarity search and VectorDBs, guardrails, memory) using Python, C++, C#, Java, CUDA, or Golang.
Experience applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
Experience building agentic AI systems and agentic workflows.
Demonstrated communication and presentation skills, including the ability to explain complex AI concepts to peers.
Recognition as an industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership.
Experience designing long-term AI infrastructure strategies balancing cost, scale, ethics, and regulatory compliance.
Experience driving organization-wide adoption of AI safety, alignment, and governance standards in collaboration with policy, risk, and legal teams.
Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact.
Experience right-sizing models, instance counts, and hardware types based on requirements such as context length, token inputs, and token outputs.

Location and Salary

Location: McLean, VA (onsite)

Salary: USD 314,800 - 359,300 per year

Additional Employment Information

Capital One may sponsor a new qualified applicant for employment authorization for this position.
Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI). Incentives may be discretionary or non-discretionary depending on the plan.
Applications are expected to be accepted for a minimum of 5 business days.
No agencies please.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
Capital One promotes a drug-free workplace.

View full job page →

1mo ago

AI Engineer 3

Capital One San Jose, CA

San Jose, CA

1mo ago Closed

$177k - $201k/yr Full time Agents Ai Engineer Artificial Intelligence

This position is no longer accepting applications (closed Oct 24, 2026).

Job Description

The AI Engineer 3 role on Capital One’s Intelligent Foundations and Experiences (IFX) team focuses on building responsible, scalable AI capabilities spanning foundation model training, LLM inference, agent workflows, evaluation, governance, and observability, with an emphasis on optimizing performance, safety, and cost efficiency.

Key Responsibilities

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve how associates work and how customers interact with Capital One.
Design, develop, test, deploy, and support AI software components, including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Apply a broad stack of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and related tools.
Develop and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput for production AI systems.
Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, including measurable performance and safety metrics.
Build scalable pipelines for training, fine-tuning, and deploying foundation or domain-specific models across multiple environments.
Collaborate with research and data engineering teams to curate high-quality datasets and improve model evaluation methodologies.
Support governance and security efforts for model traceability, lineage documentation, and version control of deployed AI assets.
Mentor junior AI engineers and promote engineering excellence, reproducibility, and responsible experimentation.

Required Qualifications

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 1 year of experience developing AI and ML algorithms or technologies.
At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java.

Technologies and Tools

AWS Ultraclusters
Huggingface
VectorDBs
PyTorch
Python, Go, Scala, CUDA, Java
Google Cloud, Azure
C++, C#, Golang
AWS
Retrieval-augmented generation (RAG)

Preferred Qualifications

Experience contributing to components of AI systems with tradeoff decisions across cost, latency, throughput, and accuracy.
4 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
Experience developing, delivering, and supporting AI services.
Experience developing AI and ML algorithms or technologies (e.g., LLM inference, similarity search and VectorDBs, guardrails, memory) using Python, C++, C#, Java, CUDA, or Golang.
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
Experience building agentic AI systems and agentic workflows.
Demonstrated ability to evaluate and optimize LLM performance using quantitative metrics such as accuracy, coherence, latency, and cost.
Hands-on experience implementing retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows.
Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems.

Compensation and Location

Location: San Jose, CA (onsite)
Salary Range: USD 176,500 - 201,400 per year

Benefits

Comprehensive, competitive, and inclusive health, financial, and other benefits to support total well-being.
Performance-based incentive compensation eligibility, which may include cash bonus(es) and/or long term incentives (LTI).

Team Overview

The Intelligent Foundations and Experiences (IFX) team brings Capital One’s vision for AI to life. The team works with partners across the company to advance the state of the art in science and AI engineering, and builds and deploys proprietary solutions central to the business, delivering value to millions of customers. The AI models and platforms empower teams across Capital One to enhance products with responsible and scalable AI in ways that drive high-leverage impact.

Ideal Candidate Profile

Enjoys building systems, takes pride in work quality, and focuses on doing the right thing.
Stays current with the latest research and can interpret scientific publications to apply novel techniques in production.
Can bring clarity to complex, undefined problems, dig into root causes, and communicate findings concisely.
Shares new ideas even when approaches are not yet proven.
Is deeply technical with strong foundations in engineering and mathematics, and can identify optimization opportunities across hardware, software, and AI.
Is resilient and capable of forging new paths to achieve business goals when the route is unknown.

Workplace and Process Notes

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
Capital One promotes a drug-free workplace.
Capital One will consider for employment qualified applicants with a criminal history consistent with applicable laws regarding criminal background inquiries.
If you need an accommodation, contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.
For technical support or questions about Capital One’s recruiting process, email Careers@capitalone.com.
Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site.
Capital One Financial consists of multiple entities; roles posted in Canada, the United Kingdom, and the Philippines correspond to the respective Capital One entities described by the company.

View full job page →

Agents Engineer Jobs

Applied AI Engineer (Full-Stack)

AI Engineer 4

Staff AI Engineer

Sr. Staff AI Engineer

AI Engineer 3

Get Agents Engineer Jobs alerts