About the Role:
As a Senior Associate, you'll lead the technical delivery of AI solutions on client engagements — architecting systems, mentoring junior developers, and ensuring what gets built is both impressive in the room and defensible in production. You'll bridge the gap between strategic AI recommendations and working software.
What You'll Do:
- Own the end-to-end technical architecture of AI-powered platforms — from data ingestion and model orchestration through to frontend experience and deployment
- Design and implement agentic AI systems: multi-step reasoning pipelines, tool-calling agents, and human-in-the-loop workflows using frameworks like LangGraph or CrewAI
- Build and optimise RAG pipelines — chunking strategies, embedding models, hybrid search, re-ranking — and evaluate retrieval quality rigorously
- Collaborate with engagement managers and clients to scope technical solutions, estimate effort, and manage delivery risk
- Set technical standards and review code across the team; mentor Associates and upskill consultants on AI tooling
- Navigate responsible AI considerations — data privacy, model explainability, audit trails — particularly in regulated industries (banking, property, government)
- Drive reusability: identify patterns across engagements and contribute to firm-wide AI accelerators and frameworks
What You Bring:
Must-have
- 2–5 years of hands-on full-stack development experience with a clear AI/ML thread
- Production-level proficiency in React or Vue (frontend) and Python or Node.js (backend)
- Deep familiarity with LLM integration patterns: function/tool calling, streaming, structured outputs, multi-turn conversation management, and prompt engineering
- Experience with agentic frameworks (LangGraph, CrewAI, AutoGen, or similar)
- Experience building RAG or semantic search systems with vector stores
- Solid understanding of API design, authentication, and cloud deployment (any major cloud provider)
- Ability to present and explain technical architecture to non-technical stakeholders
Good to have
- Exposure to AI governance, responsible AI frameworks, or regulated industry contexts (FSI, real estate, public sector)
- Familiarity with model evaluation, prompt testing pipelines, or AI observability tooling
- Prior consulting or client delivery experience is a strong plus
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