Azure Ai Search

Azure Ai Search Engineer Jobs

5 jobs found

20d ago

AI Engineer

Pointer Infotech L.L.C Columbus, OH

Columbus, OH

20d ago

$65 - $70/hr Full time Backend Developer Agentic Ai Agentic Ai Orchestration

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Job Description

Pointer Infotech L.L.C is seeking an experienced AI Engineer / Senior AI Architect to design, implement, and optimize agentic and conversational AI solutions for real-world business use. This onsite role in Columbus, OH focuses on building across both Microsoft and Google ecosystems, with a strong emphasis on Azure AI services and Google Dialogflow CX/CCAI capabilities.

The position covers end-to-end delivery, from developing AI conversational experiences and integrating APIs and web services, to training and operationalizing AI models. You will also support governance and responsible AI practices while collaborating with business subject matter experts and cross-functional technical teams.

What you’ll do

Develop agentic AI solutions, conversational agents, and virtual assistants.
Use hands-on Microsoft Foundry and Azure AI services to build and optimize AI capabilities.
Work with Azure AI Search, Azure AI Language, Power Platform, and Copilot Studio.
Develop AI conversational solutions using Google Dialogflow CX, Google Conversational Agents, and Google CCAI Services.
Build and integrate APIs and web services with AI applications.
Apply expertise in NLP, Generative AI, LLMs, and AI/ML.
Develop and maintain SharePoint Online solutions using Microsoft Power Platform.
Train, deploy, monitor, and optimize AI models over time.
Create Looker dashboards to monitor AI agent performance.
Ensure AI solutions follow security, privacy, governance, and responsible AI practices.
Collaborate with business SMEs and cross-functional technical teams to drive delivery.
Lead AI Proof of Concept (POC) initiatives and present AI solutions to stakeholders.

Required skills and qualifications

Strong expertise in Agentic AI, Conversational AI, and AI solution development.
Hands-on experience building AI solutions across Microsoft and Google ecosystems.
Mandatory: Agentic AI development using Microsoft Foundry.
Mandatory: SharePoint Online + Microsoft Power Platform.
Mandatory: Google Conversational Agents / Dialogflow CX / Google CCAI Services.
Strong programming skills in C#, .NET, JavaScript, or Python.
Bachelor’s degree in Computer Science, Information Systems, or related field, or equivalent experience.
No Visa sponsorship is available this time.

Tools and technologies

Microsoft Foundry
Azure AI services: Azure AI Search, Azure AI Language
Power Platform, Copilot Studio
Google Dialogflow CX, Google Conversational Agents, Google CCAI Services
NLP, Generative AI, LLMs, AI/ML
SharePoint Online
Looker
C#, .NET, JavaScript, Python

Location: Columbus, OH (onsite)
Compensation: USD 65 - 70 per hourly
Experience: 5+ years
Education: Bachelor’s degree in Computer Science, Information Systems, or related field, or equivalent experience

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1mo ago

Associate AI Engineer

Pogue Construction McKinney, TX

McKinney, TX

1mo ago Closed

Full time Ai Automation Ai Engineer Artificial Intelligence

This position is no longer accepting applications (closed Sep 15, 2026).

Job Description

Pogue Construction is building an AI production team that develops and supports bounded AI and automation on a governed Microsoft Fabric data platform. This early-career Associate AI Engineer role focuses on turning approved backlog items into reliable releases, partnering with business owners to drive adoption, and ensuring solutions are maintainable, measured, and safe to operate on day one.

Based in McKinney, TX with onsite expectations, the Associate AI Engineer will work across lakehouse data, enterprise semantics, and secure retrieval patterns to deliver AI-enabled capabilities that respect permissions, citations, versions, and effective dates.

What you’ll do

Develop, test, and improve bounded AI and automation capabilities using VS Code, SQL, APIs, Git, and Pogue-approved cloud services
Support solutions including permission-aware enterprise search, retrieval-augmented generation (RAG), internal assistants, workflow support, and AI-enabled analytics
Convert approved backlog items into requirements, technical tasks, acceptance criteria, and small releases that can be measured and safely supported
Create prototypes during discovery, then help convert validated prototypes into maintainable services and reusable patterns
Join design review with the Principal Solutions Architect before development starts, then carry approved designs through release
Work with Microsoft Fabric lakehouse data, governed Gold business objects, semantic models, metadata, and shared business definitions
Connect structured data and approved documents through secure APIs and retrieval patterns while preserving source permissions, citations, versions, and effective dates
Contribute to Pogue’s enterprise ontology and knowledge foundation by documenting objects, relationships, definitions, ownership, and authoritative sources
Build only on data confirmed as validated in the Gold layer
Document architecture, assumptions, decisions, data flows, interfaces, tests, deployment steps, and operating runbooks for support handoff
Evaluate accuracy, failure modes, access behavior, latency, cost, and usefulness, then convert results into release recommendations
Follow Pogue standards for identity, role-based access, data-classification, approved-model usage, logging, monitoring, and human-approval requirements
Surface uncertainty, security concerns, and data-quality issues early, proposing practical options instead of hiding risk
Work directly with business owners and subject-matter experts to understand the decision or workflow before selecting an approach
Explain tradeoffs in plain language, ask focused questions, demonstrate progress, and incorporate feedback from technical and nontechnical teammates
Support adoption through concise guides, examples, training materials, and responsive follow-through after launch
Support the AI Champions Network as solutions roll out to project teams

Required qualifications

Team player
Teachable
Curious and self-directed
Ability to write and troubleshoot code in VS Code
Working knowledge of SQL
Working understanding of REST APIs, Git-based collaboration, testing, and basic cloud concepts
Secure handling of credentials and data
Ability to explain a technical project, including decisions made, tradeoffs, and how the result was validated
Clear written communication
Ability to relate to and communicate with a diverse group of professionals
Ability to work individually and as part of a team
Self-motivated and driven
Highly organized and detail oriented
Highly analytical thinker
Positive attitude
Internal and external customer service
Willingness to ask for context when requirements are incomplete
Minimum 20 hrs of Continued Education (yearly)

Education

Bachelor’s degree in computer science, software engineering, information systems, data science, or a related field (or equivalent training) is required.

Technologies

VS Code, SQL, APIs, Git
Microsoft Fabric, OneLake
Azure AI Search, Azure OpenAI, Azure AI Foundry
Power BI
LLM applications, RAG, embeddings
Prompt or model lifecycle management
Agents or workflow automation
Protégé, OWL, RDF, SPARQL
TypeScript, C#, CI/CD, containerized services, monitoring

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1mo ago

Lead AI Engineer

Main Sail LLC Remote 🌍 Remote

Remote

1mo ago Closed

$85 - $95/hr Full time Backend Developer Manager Agent Orchestration

This position is no longer accepting applications (closed Sep 15, 2026).

Job Description

Main Sail LLC is hiring a Lead AI Engineer to design and deliver agentic AI and conversational experiences across the Google, AWS, and Microsoft ecosystems. In this remote role, you will focus on context engineering and agent design while helping ensure secure API-based access to data, strong model performance, and governance-aligned behavior.

You will lead AI architecture and implementation efforts, mentor other engineers through design and development, and help turn proof of concept work into production-ready solutions.

Key Responsibilities

Develop applications that interact with web services, APIs, and other software applications.
Mentor and lead AI design and development efforts as needed.
Perform peer reviews to confirm AI design and development standards are followed and to establish additional standards when necessary.
Design the overall structure of Agentic AI solutions, including feature definition, user flow, API development, and integration with other systems.
Implement and tune Natural Language Processing techniques to improve AI assistant understanding and response accuracy.
Train, deploy, and monitor AI models by creating and using Dashboards.
Create custom indexes, manage data sources, and tune intent matches to improve accuracy and result relevance.
Design conversational flows that deliver a seamless, intuitive experience with human-like, engaging agent interactions.
Analyze agent interaction data to find patterns, trends, and opportunities for improvement.
Prepare reports using agent performance metrics.
Identify and resolve agent performance issues through debugging and system updates.
Ensure the AI agent and conversational assistant comply with data privacy laws and maintain high security standards when handling sensitive user data.
Work with cross-functional teams including business analysts, UX designers, project managers, and business customers and business SMEs.
Collaborate with the Automation Center of Excellence (CoE) team, adhering to established standards, organization processes, and alignment to target architectures and technology roadmaps.
Ensure AI systems operate safely, transparently, and within boundaries aligned to governance policies and practices.
Plan, initiate, and spearhead proof of concept (POC) initiatives using emerging technologies.
Produce technical writing using tools such as Word, PowerPoint, Visio, SharePoint, and Excel to create presentations and white papers.

Required Qualifications

Bachelor’s degree in computer science, Information systems, or a related discipline, or equivalent and extensive related project experience.
6 years of IT experience, including at least 4 years of combined AI Conversational Agents and/or Generative AI implementation experience.
2 years of AI Engineer experience developing Google conversational agents, including CX Agent Studio and Dialogflow CX Web and Voice Virtual Assistants.
2 years developing Enterprise Looker Dashboards to monitor AI Agent performance.
2 years of AI Engineer experience in AWS, using services such as AWS Bedrock, AWS Transcribe, AWS Comprehend, Lamda, and Step Functions.

Education & Experience

Bachelor’s degree in computer science, Information systems, or related discipline; Master’s preferred.
Six years of hands-on IT design and implementation experience, with knowledge in at least two technical disciplines: application development, network design, middleware, servers and storage, database management, operations, AI and machine learning fundamentals.
Experience in natural language processing (NLP) and large language model (LLM) integration.
Agentic AI Developer Experience using Microsoft Foundry is preferred.
Experience developing and maintaining SharePoint online solutions using MS Power Platform is preferred.
Google and AWS certifications relevant to this role are preferred.

Tools & Technologies

Google: Google CX Agent Studio, Google Conversational Agents, Google Dialogflow CX, Google CCAI Services
Analytics: Looker Dashboards
AWS: AWS Bedrock, AWS Transcribe, AWS Comprehend, Lamda, Step Functions
Microsoft: Microsoft Foundry, Azure AI Search, Azure AI Language Service, Microsoft Power Platform, Microsoft CoPilot Studio, Office 365, SharePoint
Languages & Platforms: C#, .NET, JavaScript, Python
Writing/Collaboration: Word, PowerPoint, Visio, Excel
AI/NLP: NLP, LLM, Natural Language Processing, Artificial intelligence and machine learning fundamentals

Compensation & Location

Location: Remote (remote)
Pay: USD 85 - 95 per hourly

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1mo ago

Lead AI Engineer

Vytwo Dallas, TX

Dallas, TX

1mo ago Closed

Full time Manager Artificial Intelligence Azure

This position is no longer accepting applications (closed Sep 11, 2026).

Job Description

Vytwo is hiring a Lead AI Engineer in Dallas, TX to help build and run production-ready AI applications. The role focuses on designing end-to-end data and AI pipelines and deploying ML and Generative AI workloads on Azure Databricks and related Azure infrastructure.

You will take models from experimentation to production by implementing robust ETL/ELT workflows, CI/CD for Databricks, and the monitoring and governance needed for reliable operations.

What you’ll do

Design and build end-to-end data and AI pipelines using Azure Databricks.
Develop resilient ETL/ELT workflows with Python (PySpark) and SQL.
Create CI/CD pipelines for Databricks deployments, including jobs, notebooks, and workflows.
Integrate Databricks with Azure services such as Data Lake, Blob Storage, Key Vault, Azure OpenAI, and Azure Functions.
Optimize Databricks workloads for performance, cost, and reliability.
Build reusable, modular code for pipeline and AI components.
Work with data scientists and platform teams to move models from experimentation to production.
Implement logging, monitoring, and error handling for production pipelines.
Develop and deploy ML and Generative AI models including LLMs, embeddings, and RAG pipelines for NLP, computer vision, and predictive analytics.
Fine-tune LLMs using LoRA/QLoRA and integrate with Azure OpenAI or Hugging Face models.
Implement vector search and retrieval pipelines using FAISS or Azure Cognitive Search.
Apply responsible AI practices, including bias detection and model governance.

What you’ll need

Azure Databricks experience with jobs, workflows, clusters, and Unity Catalog (preferred).
Strong Python experience with a PySpark-heavy focus.
SQL skills including complex joins, window functions, and analytical querying.
Hands-on experience with Azure cloud services and concepts including ADLS Gen2, ADF, Key Vault, and IAM.
Experience with pipeline orchestration and deployment including CI/CD and environment promotion.
Azure DevOps experience.
Strong understanding of ML lifecycle and MLOps best practices.
Experience deploying models using MLflow or similar frameworks.

Tools and technologies

Azure Databricks, Databricks workflows, Databricks jobs, Databricks notebooks, Unity Catalog
Azure cloud infrastructure, Azure Data Lake, Blob Storage, Key Vault, Azure OpenAI, Azure Functions
Python, PySpark, SQL, ETL/ELT
CI/CD pipelines, logging, monitoring
MLflow, LoRA, QLoRA, Hugging Face models
FAISS, Azure Cognitive Search
NLP, computer vision, predictive analytics, vector search, RAG pipelines
Azure DevOps

Good to have (strong advantage)

Experience with ML and Generative AI workloads on Databricks.
RAG, embeddings, or inference pipeline experience.
Experience with Terraform / ARM / Bicep.
Databricks Asset Bundles experience.
Experience with Airflow or ADF orchestration.
Production monitoring and cost optimization experience.
Knowledge of LangChain or similar AI application development frameworks.
Experience with Azure AI services including Azure Machine Learning and Azure Cognitive Services.

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1mo ago

Sr Machine Learning Engineer

System One Pittsburgh, PA

Pittsburgh, PA

1mo ago Closed

Contract Senior Ai Ml Artificial Intelligence

This position is no longer accepting applications (closed Aug 21, 2026).

Job Description

System One offers an onsite, contract-to-hire Senior Machine Learning Engineer role with opportunities across Pittsburgh, Dallas, and Cleveland. This senior position centers on production ML models, GenAI and LLM workflows, governance, and release planning within finance projects. The engagement is onsite five days a week, with a clear path to permanent placement for a candidate with 10+ years of experience.

What you will gain

Onsite, five days a week across Pittsburgh, Dallas, and Cleveland
Contract-to-hire engagement with potential for permanent placement
Hands-on work on production ML models and GenAI / LLM initiatives, with governance and release planning in finance

Responsibilities

Continuous support of models deployed to production applications
Internal client consultation to elicit and collect requirements, and communicate and align the technical team toward delivery
Release planning, coordination, and hands on support throughout release windows

Requirements

Experience implementing production solutions that leverage generative AI and LLMs
Machine learning model solution design, build, orchestration and implementation
Experience building solutions with model governance, risk management, and regulatory adherence at top of mind
GPT 5.x
Langchain
RAG / RAGAS

Technologies

GPT 5.x
Langchain
RAG / RAGAS
Azure AI Search
AI Agent Service
Document Intelligence
Content Safety
Microsoft Agent Framework
Foundry
Redis
Elasticsearch
Arize
Deepeval
ChromaDB
Langgraph

Location and engagement details

Locations: Pittsburgh, PA; Dallas, TX; Cleveland, OH

Work status: Onsite 5 days a week

Duration: Contract to Hire

Experience: 10+ years

Industry: Finance / Banking

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Azure Ai Search Engineer Jobs

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