AI Engineer — Generative AI Agentic Workflows IRC300522

Description

Customer is a US medical Company that is dedicated to transforming patient’s lives at scale by being the driving force to decentralize the delivery of safe care into their homes or other preferred sites of care.
Project provides health systems with all that is needed to safely care for patients, including the clinical protocols, reimbursement model, platform technology, and fulfillment of all the clinical services required in the home through partners. Clinicians and patients broadly prefer this model over traditional care; both clinical and financial outcomes are improved as compared to traditional care.

Requirements

Must have:

• Strong Python skills and solid Computer Science / software engineering fundamentals
• Strong hands-on experience with LLMs and generative AI: building, integrating, and shipping LLM-powered applications to production (not traditional ML/model training)
• Practical experience designing and building agentic workflows / AI agents (e.g., LangChain, LlamaIndex, Bot Framework, Claude/Bedrock agents, or similar)
• Experience with agent and LLM evaluation: measuring quality, grounding, and reliability of AI solutions
• REST APIs and integration of AI solutions with enterprise data sources (SharePoint, Confluence, Jira, etc.)
• Delivery-focused seniority: a mature engineer able to own solutions end-to-end and grow into a team lead role
• Excellent communication and collaboration skills: open-minded, comfortable in stakeholder meetings, works well in a remote setup

Nice to have:

• Microsoft ecosystem experience: Copilot Studio / Power Platform, M365, Azure OpenAI
• AWS Bedrock and Claude-based solutions (the client is actively rolling out Claude through Bedrock)
• Some data engineering experience (pipelines, data preparation for RAG/grounding — no need to be a guru)
• Experience in regulated environments (healthcare a strong plus)
• Azure Functions, CI/CD pipelines, DevOps practices
   

Job responsibilities

• Design, build, and productionize generative AI solutions and agentic workflows for company-wide use (engineering and non-engineering users)
• Contribute to the three major AI engines currently in development, including supporting and pairing with existing team members
• Build and run evaluations of AI agents: quality, grounding against private knowledge bases, and reliability
• Ground AI solutions in enterprise knowledge sources (SharePoint, Confluence, Jira) with appropriate access and security controls
• Write custom code (Python, APIs) to extend beyond low-code tool limitations where needed
• Assess and advise on platform/tooling choices (Copilot Studio vs. Claude/Bedrock vs. custom), including cost and licensing trade-offs
• Participate actively in stakeholder meetings; translate business needs into delivered AI solutions
• Grow into a team lead role: set engineering direction, mentor AI enthusiasts on the team, and enable the sponsor to step back into a strategic role