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About the Role
As a Forward Deployed Lead / Principal Engineer (FDE) with an AI & Agentic Engineering focus, you will own the technical direction and delivery of major enterprise AI programs. You will architect agentic systems and generative AI applications, align enterprise goals with target-state AI architectures, and guide the team’s technical direction. You combine deep expertise in agentic AI systems, RAG, and applied software engineering with strong consulting acumen, establishing AI governance frameworks and championing sound engineering practices.
Responsibilities
- Design and build agentic AI applications and multi-agent workflows, along with the frameworks that run them, for enterprise use cases
- Build RAG pipelines and integrate LLM APIs, vector databases, and MCP (Model Context Protocol) tooling
- 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, scaling, and MLOps/LLMOps
- Define AI governance and responsible-use guardrails: data privacy boundaries, LLM governance, and policy enforcement (OPA/Rego)
- Instrument AI applications for observability (OpenTelemetry, Prometheus) so behaviour and cost stay visible in production
- Translate enterprise requirements into AI solution roadmaps for senior stakeholders
- Capture field learnings, codify reusable agentic patterns, and mentor engineers hands-on
- Provide architectural oversight across multi-disciplinary workstreams, staying close enough to unblock the team directly
Requirements
- 8–10+ years in software or solution engineering, with a track record of shipping AI systems in client-facing engagements
- Strong Python engineering (FastAPI), with solid SDLC practices: design, testing, code review, CI/CD, Git & GitHub
- Hands-on experience with agentic AI frameworks (examples include LangGraph, CrewAI, AutoGen, 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) for data modelling behind AI applications
- Hands-on familiarity with modern AI coding copilots (e.g. Claude, Codex, Cursor)
- Strong stakeholder communication, translating AI capability into business outcomes for senior stakeholders
- Familiarity with observability instrumentation for AI systems (OpenTelemetry, Prometheus)
- Experience with AI/ML frameworks (TensorFlow, 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
- Understanding of LLM governance: data privacy, guardrails, and responsible-use controls
- T-shaped profile: deep expertise in AI engineering, broad understanding across software engineering and technical consulting
- Willingness to travel and work on customer premises as required
Skills
- AI & Agentic Engineering
- Generative AI
- Agentic AI systems
- RAG
- Applied software engineering
- Python
- FastAPI
- SDLC practices
- Git
- GitHub
- Agentic AI frameworks
- LangGraph
- CrewAI
- AutoGen
- Semantic Kernel
- OpenAI’s Agents SDK
- Google’s Agent Development Kit
- MCP (Model Context Protocol)
- LLM APIs
- Vector databases
- Unstructured data processing
- Ontology extraction
- Relational databases
- Graph databases
- Postgres
- Neo4j
- AI coding copilots
- Claude
- Codex
- Cursor
- Stakeholder communication
- Observability instrumentation
- OpenTelemetry
- Prometheus
- AI/ML frameworks
- TensorFlow
- PyTorch
- Hugging Face
- Open-source AI ecosystem
- Image understanding
- OCR
- Policy-as-code
- OPA/Rego
- LLM governance
- Data privacy
- Guardrails
- Responsible-use controls
Work Type
- Hybrid
Experience Level
- 8-10+ years
Education Level
- Degree in Computer Science, Data Science, Informatics, Engineering, Physics, Mathematics, or a related discipline — or equivalent professional experience
Benefits
- Flexible, supportive environment
- Well-being is prioritized
- Potential can thrive
- Be Well programs
- Financial health support
- Mental health support
- Physical health support
- Social health support
- Impactful work
- Meaningful projects
- Career path tools
- Personalized development goals
- Continuous feedback
- Cutting-edge learning opportunities
- Certifications with Microsoft, Google, and Amazon
- Coaching
- Hands-on experiences
About the Company
- Kyndryl runs and reimagines the mission-critical technology systems that drive advantage for the world’s leading businesses.
- Kyndryl is 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.
- Kyndryl focuses on ensuring all Kyndryls feel included and welcomes people of all cultures, backgrounds, and experiences.
- Kyndryl believes in growth and is excited to see what candidates can bring.
- At Kyndryl, employee feedback has told us that our number one driver of employee engagement is belonging.
- That sense of belonging — being a valued, respected, trusted member of the team — is fundamental to Kyndryl's culture and fueling great experiences for our customers.
- Kyndryl's dedication to welcoming everyone into the company means that Kyndryl gives you the ability to thrive and contribute to our culture of empathy and shared success.
- Kyndryl offers a dynamic, hybrid-friendly culture that supports your well-being and empowers you to grow.
Equal Opportunity
- Kyndryl welcomes people of all cultures, backgrounds, and experiences.
- Even if you don’t meet every requirement, we encourage you to apply.
- Kyndryl gives you the ability to thrive and contribute to our culture of empathy and shared success.
- Kyndryl is committed to helping you thrive.