Forward Deployed Engineer – AI, Agentic Engineer

Kyndryl

. Own delivery of AI applications for complex customer engagements .

Posted 9/15/2026full-timeLondon • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI application delivery, including Python programming, FastAPI development, and AI/ML integration. Proficient in building RAG pipelines, managing data governance, and applying observability practices in AI systems.

Highest-signal resume keywords

Python EngineeringFastAPI DevelopmentAI/ML IntegrationRAG Pipeline DevelopmentData Governance

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Hard Skills

Software EngineeringAPI DesignSDLC PracticesAgentic AI FrameworksRelational DatabasesGraph DatabasesDockerAI/ML FrameworksImage UnderstandingPolicy-as-Code

Soft Skills

Trusted AdvisorClient GuidanceCollaboration

Tools & Technologies

OpenTelemetryPrometheusGitGitHubMCPClaudeCodexCursorTensorFlowPyTorch

Industry Keywords

AI GovernanceData PrivacyLegacy ModernisationObservabilityTechnical Consulting

Tech Stack

Tools & technologies

DockerNeo4jPostgresPrometheusPythonPyTorchSDLCTensorflow

About the role

Key responsibilities & impact

Own delivery of AI applications for complex customer engagements
Translate business challenges into agentic AI applications and generative AI use cases
Build and iterate agentic workflows, RAG pipelines, and LLM API integrations
Process unstructured data into condensed, structured knowledge, including ontology extraction
Write production-grade Python services with FastAPI
Apply design, testing, code review, and CI/CD practices
Work with relational and graph databases to model and serve data behind AI applications
Collaborate with platform engineering throughout hosting and MLOps/LLMOps deployment
Define AI governance and responsible-use guardrails, including data privacy boundaries and OPA/Rego policy enforcement
Instrument AI applications for observability using OpenTelemetry and Prometheus
Guide clients through legacy modernisation into AI-enabled workflows
Troubleshoot performance and reliability issues
Capture deployment learnings and share best practices with core AI platform teams
Contribute code, reusable agentic patterns, and feedback to core platform teams

Requirements

What you’ll need

5+ years of hands-on software engineering experience, with exposure to AI/ML integration and API design
Strong Python engineering and FastAPI experience
Solid SDLC practices, including design, testing, code review, CI/CD, Git, and GitHub
Hands-on experience with agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI’s Agents SDK, or Google’s Agent Development Kit
Experience with MCP (Model Context Protocol)
Practical experience building RAG/LLM-based pipelines and working with vector databases
Experience with relational and graph databases such as Postgres and Neo4j
Experience with Docker
Familiarity with modern AI coding copilots such as Claude, Codex, or Cursor
Familiarity with observability instrumentation for AI systems, including OpenTelemetry and Prometheus
Experience with AI/ML frameworks such as TensorFlow or PyTorch and the Hugging Face/open-source AI ecosystem
Experience with image understanding and OCR
Working knowledge of policy-as-code, including OPA/Rego
Understanding of LLM governance, data privacy, guardrails, and responsible-use controls
Experience guiding clients through legacy application modernisation into AI-enabled workflows
Solid technical expertise in AI engineering and broad understanding across enterprise IT and technical consulting
Ability to serve as a trusted advisor and translate business requirements into technical roadmaps
Willingness to travel and work on customer premises as required
Degree in Computer Science, Informatics, Data Science, Engineering, Physics, Mathematics, or a related discipline — or equivalent professional experience

Benefits

Comp & perks

Flexible, supportive environment
Well-being support through Be Well programs covering financial, mental, physical, and social health
Hybrid-friendly culture
Personalized development goals and continuous feedback
Access to cutting-edge learning opportunities
Certifications with Microsoft, Google, and Amazon
Coaching and hands-on development experiences
Career-path and professional development tools
Employee referral opportunity