22 hours ago
London, United KingdomStaff+
Responsibilities
- Design and build agentic AI applications, multi-agent workflows, and supporting frameworks for enterprise use cases.
- Build RAG pipelines and integrate LLM APIs, vector databases, and Model Context Protocol tooling.
- Process unstructured data into structured knowledge, including ontology extraction.
- Develop production-grade Python and FastAPI services using sound design, testing, code review, CI/CD, and Git practices.
- Work with Postgres, Neo4j, and other relational and graph databases to model and serve data for AI applications.
- Collaborate with platform engineering on hosting, scaling, deployment, MLOps, and LLMOps.
- Define AI governance, privacy boundaries, responsible-use guardrails, and policy enforcement using OPA/Rego.
- Instrument AI applications with OpenTelemetry and Prometheus for production observability and cost monitoring.
- Translate enterprise requirements into AI solution roadmaps for senior stakeholders.
- Codify reusable agentic patterns, mentor engineers hands-on, and provide architectural oversight across multidisciplinary workstreams.
Requirements
- Requires 8–10+ years of software or solution engineering experience and a track record of shipping AI systems in client-facing engagements.
- Requires strong Python and FastAPI engineering skills with experience in design, testing, code review, CI/CD, Git, and GitHub.
- Requires hands-on experience with agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI’s Agents SDK, or Google’s Agent Development Kit, plus MCP.
- Requires practical experience building RAG and LLM-based pipelines and working with vector databases.
- Requires experience with relational and graph databases such as Postgres and Neo4j.
- Requires familiarity with AI coding copilots such as Claude, Codex, or Cursor.
- Requires strong stakeholder communication and the ability to translate AI capabilities into business outcomes.
- Preferred qualifications include OpenTelemetry and Prometheus experience, TensorFlow or PyTorch experience, familiarity with Hugging Face and the open-source AI ecosystem, image understanding and OCR experience, and OPA/Rego policy-as-code knowledge.
- Preferred candidates understand LLM governance, data privacy, guardrails, responsible-use controls, software engineering, and technical consulting.
- Requires a degree in Computer Science, Data Science, Informatics, Engineering, Physics, Mathematics, or a related discipline, or equivalent professional experience.
- Willingness to travel and work on customer premises is preferred.
Benefits
- Hybrid-friendly work culture with financial, mental, physical, and social well-being programs.
- Career development support including personalized development goals, continuous feedback, certifications with Microsoft, Google, and Amazon, coaching, and hands-on learning opportunities.
- Inclusive culture focused on belonging, empathy, professional growth, and shared success.
- Willingness to travel and work at customer premises may be required depending on the engagement.
Tech Stack
Categories
Forward Deployed
About Kyndryl
Kyndryl is a public IT services company that designs, runs, and modernizes mission-critical infrastructure for large enterprises and governments. Spun off from IBM in 2021, it is headquartered in New York City and trades on the NYSE (ticker: KD). The company provides managed infrastructure, cloud migration and operations across AWS, Azure, and Google Cloud, plus mainframe, network, security, data, and digital workplace services.