Forward Deployed Engineer - Ai & Agentic Engineer

At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive.

As a Forward Deployed Engineer (FDE) with an AI & Agentic Engineering focus (Band
8), you own delivery of AI applications for complex customer engagements, including the agentic systems and generative AI features that go into production in close collaboration with platform engineering. You translate business challenges into technical solutions, build and iterate AI applications, and work hand-in-hand with the platform engineers on the team throughout design, build, and deployment. You’re accountable for what you build, including how well it holds up once people are actually using it.

You operate with significant autonomy, bring deep expertise in agentic AI architectures and applied software engineering, and confidently bridge engineering rigour with business value. You use modern AI development tools and sound engineering practice across the full delivery lifecycle to accelerate learning, improve quality, and deliver measurable impact.

• Translate business challenges into agentic AI applications and generative AI use cases
• Build and iterate AI applications: agentic workflows and the frameworks that run them, RAG pipelines, and LLM API integrations
• Process unstructured data into condensed, structured knowledge, including ontology extraction
• Write production-grade Python services (FastAPI) with solid engineering practices: design, testing, code review, CI/CD
• Work with relational and graph databases (e.g. Postgres, Neo4j) to model and serve data behind AI applications
• Work closely with platform engineering throughout deployment — hosting and MLOps/LLMOps — without owning that infrastructure yourself
• Define AI governance and responsible-use guardrails: data privacy boundaries and policy enforcement (OPA/Rego)
• Instrument AI applications for observability (Open Telemetry, Prometheus)
• Guide clients through legacy modernisation into AI-enabled workflows, troubleshooting performance and reliability issues
• Capture deployment learnings and share best practices to inform core AI platform frameworks
• Contribute code, reusable agentic patterns, and feedback to core platform teams

• 5+ years of hands‑on software engineering experience, with exposure to AI/ML integration and API design
• Strong Python engineering (FastAPI), with solid SDLC practices: design, testing, code review, CI/CD, Git & Git Hub
• Hands‑on experience with agentic AI frameworks (examples include Lang Graph, CrewAI, Auto Gen, Semantic Kernel, OpenAI’s Agents SDK, and Google’s Agent Development Kit) and MCP (Model Context Protocol)
• Practical experience building RAG/LLM-based pipelines and working with vector databases
• Experience with relational and graph databases (e.g. Postgres, Neo4j) and Docker for building and running AI applications
• Hands‑on familiarity with modern AI coding copilots (e.g. Claude, Codex, Cursor)

• Familiarity with observability instrumentation for AI systems (Open Telemetry, Prometheus)
• Experience with AI/ML frameworks (Tensor Flow, PyTorch) and the Hugging Face / open‑source AI ecosystem
• Experience with image understanding and OCR
• Working knowledge of policy‑as‑code (OPA/Rego) for AI governance and guardrails
• Under…