Job Description
About the Client:
We are partnering with a fast-growing, globally recognised Data & Generative AI consulting firm that works with Fortune 1000 and large enterprise clients across industries such as FMCG, Manufacturing, Automotive, and Supply Chain .
About the Role:
This is a principal-level, hands-on engineering role for someone who wants to shape GenAI platforms at scale , not just experiment with models. You will play a critical role in defining architecture, setting engineering standards, and building production-grade GenAI systems used by enterprise customers.
As a Principal Full Stack AI Engineer, you will:
Play an instrumental role in shaping the Generative AI vision, strategy, and technical architecture Architect, build, and scale production-ready GenAI applications and platforms Design and develop robust backend systems and APIs for AI-driven products and agent-based frameworks Integrate LLMs into secure, scalable, enterprise-grade systems Build reusable frameworks for model development, deployment, monitoring, and lifecycle management Implement monitoring, logging, tracing, and alerting across GenAI systems Define and enforce guardrails, compliance rules, and governance workflows
(e.g. approval chains, staged rollouts, controlled production releases) Create developer templates, documentation, and sandbox environments to enable rapid experimentation and onboarding Ensure GenAI applications are safe, reliable, and well-tested before release through validation and peer review processes Champion strong software engineering practices across teams and projects Mentor senior engineers and act as a technical leader and problem-solver Python,Data,API Development,API,Full life cycle experience,Agents,Architecture
Looking for someone who brings both depth and breadth :
Proven experience leading AI or GenAI projects end-to-end , from concept to production Strong professional background in software engineering , especially backend systems and APIs Hands-on expertise with: Python (Django or similar frameworks) and JavaScript / TypeScript (React) Solid understanding of: Backend architectures; REST / GraphQL APIs; Data modelling and system design Experience with containerisation and cloud platforms (Docker, GCP, Azure, or similar) Exposure to agentic and orchestration frameworks such as: LangChain; LangGraph; Semantic Kernel Practical experience with SQL and NoSQL databases Strong foundation in software design principles and scalable system architecture Demonstrated leadership and mentoring capability Excellent communication skills — able to explain complex AI concepts to non-technical stakeholders Strategic mindset with a passion for innovation, problem-solving, and building at scale Broad SME-level exposure to AI, ML, deep learning, data science, analytics, big data, cloud, mobile, and full-stack technologies Hands-on experience analysing large, complex datasets to drive business insights
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