Senior Agentic AI Engineer

Location: Glendale AZ

Onsite Flexibility: Hybrid 3 days onsite per week

• Position Type: Contract
• Contract Duration: 12 months
• Pay Rate: $51.40$66.71 / Hour (USD)
• Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

We are seeking a hands-on Senior Agentic AI Engineer to design build and operate production-grade Agentic AI Decision Intelligence and Retrieval-Augmented Generation solutions on Microsoft Azure for the Digital Supply Chain Systems organization. The role will support diverse and evolving DSCS business requirements by developing reusable scalable secure and explainable enterprise AI capabilities.

• Design and build production-grade single-agent and multi-agent systems in Azure AI Foundry capable of orchestrating reasoning planning tool usage and workflow execution.
• Architect scalable Generative AI solutions leveraging Azure AI Foundry Azure OpenAI Azure AI Search and other enterprise AI services.
• Build and govern Retrieval-Augmented Generation (RAG) architectures using structured and unstructured enterprise data sources including embeddings vector/hybrid search chunking metadata filtering reranking grounding and citations.
• Develop secure reliable integrations between agents and enterprise systems using Model Context Protocol (MCP) REST APIs relational databases and event-driven services.
• Design Natural Language to SQL (NL2SQL) capabilities ensuring accuracy explainability and secure access to enterprise data.
• Define semantic-layer strategies that enable AI agents to understand enterprise data models business metrics terminology and relationships.
• Architect decision intelligence capabilities that combine enterprise data business context analytics and AI reasoning to support informed decision-making.
• Establish reusable frameworks for impact analysis dependency identification prioritization recommendation generation and decision traceability.
• Ensure AI-generated recommendations are explainable evidence-based grounded in authoritative enterprise data and aligned with business objectives.
• Define and automate evaluation methodologies for response quality reasoning quality recommendation relevance business usefulness and user trust including golden datasets LLM-based evaluation and regression evals wired into CI/CD.
• Implement guardrails and Responsible AI controls: input/output content safety PII protection grounding checks authorization boundaries and human-in-the-loop escalation paths.
• Establish governance security safety transparency and compliance standards for enterprise AI solutions.
• Implementation of observability and monitoring frameworks for AI applications including quality performance reliability and adoption metrics plus traces tool calls latency token usage and cost.
• Optimize solutions for cost and latency through model selection prompt and context engineering caching and workload right-sizing.
• Drive architectural decisions for scalable cloud-native AI platforms using modern software engineering DevOps and MLOps/LLMOps practices.
• Define technical standards reference architecture and reusable frameworks for AI agents reasoning systems and decision-support applications.
• Mentor engineers and provide technical framework on Agentic AI decision intelligence software architecture and enterprise AI best practices.
• Partner with business stakeholders and domain experts to transform complex business requirements into reusable AI capabilities.
• Collaborate with data engineering teams to develop AI-ready data products semantic models metadata frameworks and enterprise knowledge layers.
• Stay current with emerging AI technologies frameworks and industry practices evaluating their applicability within DSCS and enterprise environments.

• Strong programming proficiency in Python; working knowledge of TypeScript/ or a comparable language for application services.
• Strong software engineering background with experience designing and deploying production-grade cloud applications.
• Hands-on experience building Generative AI and RAG applications with Azure AI Foundry Azure OpenAI Azure AI Search LLM APIs embeddings vector or hybrid search knowledge retrieval grounding and citations.
• Experience with Agentic AI frameworks such as Microsoft Agent Framework Semantic Kernel LangGraph AutoGen or comparable frameworks including single-agent and multi-agent systems tool calling MCP-based tool integration and human-in-the-loop controls.
• Experience building natural language to SQL or conversational analytics solutions including schema and metadata modeling query generation query validation and grounding answers in retrieved data.
• Experience designing or contributing to decision intelligence systems that combine AI analytics business context and operational workflows to improve decision quality and business outcomes.
• Experience evaluating and improving agent quality through prompt engineering test datasets LLM-based evaluation safety checks reasoning-quality assessment and production feedback loops.
• Strong knowledge of LLMOps CI/CD Docker and Kubernetes observability and production operations for AI applications.
• Working knowledge of core Azure platform services: AKS or Azure Container Apps Azure Functions API Management Entra ID Key Vault and Azure SQL or Cosmos DB.
• Good understanding of RESTful APIs asynchronous patterns secure integrations relational databases SQL SQL/NoSQL data stores and data engineering or ETL pipelines.
• Experience with enterprise-scale secure AI deployments including identity authorization data privacy compliance and production monitoring.
• Strong analytical problem-solving collaboration and communication skills.

• Experience with Microsoft Fabric Azure Databricks or Azure Data Factory for AI-ready data pipelines.
• Exposure to Copilot Studio Power Platform or Teams-based agent experiences.
• Experience with model fine-tuning (e.g. LoRA/QLoRA) prompt caching and token/cost optimization at scale.
• Supply chain domain knowledge (procurement expediting logistics materials management) or familiarity with ERP data such as Oracle EBS or SAP.
• Front-end experience with React and TypeScript for building agent-facing user interfaces.
• Microsoft certifications such as Azure AI Engineer Associate (AI-102/AI-103) or Azure Solutions Architect (AZ-305).

• Bachelors degree in Computer Science or a related field (Masters preferred)

• 8 years of relevant software engineering experience.
• 3 years of hands-on experience developing Generative AI machine learning intelligent automation or LLM-based applications including substantial recent experience with Agentic AI.

• Medical Vision and Dental Insurance Plans
• 401k Retirement Fund

This client is a privately held global leader in engineering procurement and construction with more than 125 years of experience delivering complex infrastructure projects across 160 countries on all seven continents. The organization has completed more than 25000 projects spanning energy and industrial infrastructure nuclear and environmental remediation government services and mining and metals at a scale that includes national governments global energy companies and the worlds largest public agencies among its clients. With a Glassdoor rating of 4.0 stars from nearly 2500 employee reviews and 78 percent of employees recommending the company to a friend the organization has earned strong employee endorsement and a 4.0-star rating for career opportunities one of the highest in its sector. Teams here include civil and structural engineers project controls specialists procurement managers nuclear and environmental remediation professionals and a growing cohort of enterprise IT ERP and AI engineering talent supporting the organizations digital transformation at industrial scale.

GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking financial services technology life sciences biotech utilities and retail sectors throughout the U.S. and Canada.

Job Number: 26-13801 Industry: Engineering

#LI-Hybrid #LI-GTT