Description :

Job Title : Lead SME GenAI DevOps

Contract Duration : 6 Months (Contract)

Job Summary :

We are seeking a high-impact Lead Subject Matter Expert (SME) GenAI DevOps to take end-to-end ownership of a GenAI Platform. This role blends deep technical execution with technical leadership and DevOps best practices, and is suited for a senior professional who can architect, build, operate, and continuously improve GenAI systems at scale.

The ideal candidate will bring strong expertise in LLMs, Prompt Engineering, and Retrieval-Augmented Generation (RAG) architectures, along with hands-on development experience across FastAPI (Python), Node.js, React, and Azure-based deployments. Beyond development, this role will lead platform transitions, monitor system performance, and act as the primary technical authority for GenAI initiatives.

Key Responsibilities :

GenAI Platform Ownership & Architecture :

- Act as the Lead SME for the GenAI platform, owning architecture, implementation, and operational stability.

- Design, implement, and optimize LLM-powered systems, including Prompt Engineering and RAG pipelines.

- Define and enforce best practices across the RAG lifecycle: chunking strategies, embeddings, retrieval logic, and response augmentation.

Backend & API Development :

- Build and maintain scalable backend services using Python (FastAPI) and Node.js.

- Design and expose secure, high-performance APIs to support GenAI workflows and downstream consumers.

- Integrate LLMs, vector databases, and enterprise systems through robust backend services.

Frontend & AI-Driven UI Enablement :

- Collaborate on or contribute to React-based UI components for AI-driven applications.

- Ensure seamless integration between frontend experiences and GenAI backend services.

Vector Databases & Semantic Search :

- Implement and optimize vector search solutions using technologies such as pgvector, HNSW, or equivalent.

- Manage embeddings, indexing strategies, and retrieval performance to ensure accuracy and scalability.

- Continuously tune semantic search and relevance scoring for production workloads.

DevOps, Reliability & Operations :

- Apply and champion DevOps best practices for GenAI systems, including CI/CD, environment management, and monitoring.

- Monitor system performance, latency, reliability, and cost efficiency of AI workloads.

- Lead platform transitions, upgrades, and operational improvements with minimal disruption.

- Ensure production readiness, scalability, and observability of GenAI services.

Leadership & Stakeholder Management :

- Serve as the primary technical point of contact for GenAI initiatives.

- Provide technical leadership during cross-team transitions and complex problem-solving scenarios.

- Collaborate with product, engineering, and business stakeholders to align technical solutions with business goals.

- Mentor team members and guide best practices in GenAI development and operations.

Required Skills & Experience :

Must Have :

- Strong expertise in LLMs, Prompt Engineering, and Retrieval-Augmented Generation (RAG) patterns.

- Hands-on experience with RAG architectures, including chunking, embeddings, retrieval, and augmentation.

- Proficiency in Node.js for backend integration and Python (FastAPI) for API development.

- Frontend engineering exposure using React for AI-driven UI components.

- Deep experience with vector databases, semantic search, and embeddings (pgvector, HNSW, or similar).

- Solid understanding and implementation of DevOps practices for AI/ML platforms.

- Experience operating and monitoring production-grade AI systems.

Nice to Have / Preferred Skills :

- Strong leadership and stakeholder management capabilities.

- Experience leading technical transitions or platform modernization initiatives.

- Prior exposure to Azure-based AI or cloud platforms.

- Experience in enterprise-scale GenAI deployments.