Technical PM- AI

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

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Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

Role Summary

We need a hands-on Technical Delivery Lead/Tech PM to drive delivery for an AI solutions Pod building production-grade AI capabilities (ML and Gen AI), including RAG-based solutions. The role requires someone who can plan and deliver based on component interactions (data --> embeddings/vector stores --> retrieval --> LLM orchestration --> evaluation --> deployment), set guardrails, and guide decisions on when ML/Gen AI is appropriate vs when it isnt.

This person should be trusted to represent the pod in senior forums and be able to run delivery across multiple pods/squads when needed.

Key responsibilites

1. Own end-to-end delivery of AI based solutions: roadmap, milestones, dependency management, delivery governance across 1-2+ pods
2. solution planning based on architecture: create delivery plans that reflect how components integrate (data ingestion, vectorization, retrieval, model endpoints, orchestration, UI/API,monitoring)
3. Stakeholder Leadership: represent the team in architecture reviews, governance and senior stakeholder updates, provide crisp reporting and decision options.
4. Delivery excellence: manage risks, NFRs (latency, resilience, security), release planning, production readiness, incident learnings
5. Technical oversight of ML+Gen AI:

•                         - Differentiate and select approaches: classical ML vs Gen AI vs hybrid patterns (eg: RAG + ML ranking / classification)
•                          - Define where ML adds value (prediction, scoring, classification) and where Gen AI adds value (generation, summization, extraction, conversational interfaces)

1. RAG delivery Leadership

•                               - Chunking strategies, embedding model selection, indexing, retrieval patterns, reranking, citation/attribution, freshness updates
•                                 - work with teams on relevance evaluation and hallucination reduction patterns

1. Guardrails and controls

•            - Define Guardrails for data usage, sensitive data handling, access controls, content safety, prompt/response filtering, and human-in-the-loop where required
•               - Drive policies/standards for model usage, tool access, logging, monitoring, and approval gates

**Must have experience and capabilities:**

1. 8-10+ years in technical delivery / engineering-led programme delivery
2. Proven delivery of multiple AI use cases into production (not only POCs)
3. Hands-on technical comfort: able to work with engineers on design decisions, challenge approaches, and translate requirements into implementable epics/stories
4. strong understanding of

•                                            - ML Lifecycle (data prep, training/validation, bias considerations, evaluation, deployment, monitoring drift)
•                                            - GenAI Lifecycle (model selection, orchestration, prompt strategies at a high level, evaluation, safety)
•                                            - RAG Patterns (vector stores, embeddings, retrieval, reranking, grounding, citations)

The rest of this description is on the employer’s own page.