AI Tech Lead

Role & responsibilities

Lead the architecture, design and development of AI/ML and Generative AI products and

platforms.

Build production-grade LLM applications, RAG pipelines, AI Agents and multi-agent systems.

Design scalable RAG and Vector Search architectures, covering ingestion, embeddings, retrieval,

reranking and context optimization.

Evaluate and integrate LLMs, open-source models and AI platforms, balancing quality, latency,

cost, privacy and scalability.

Drive model fine-tuning, GPU inference, model serving and performance optimization for

production workloads.

Establish LLM evaluation, observability and monitoring practices to continuously improve AI

quality and reliability.

Design highly scalable, reliable and cost-efficient AI services across AWS, Azure and/or Google

Cloud.

Mentor engineers, conduct technical reviews and provide technical direction and architectural

leadership across AI initiatives.

Technical Skills

GenAI / LLM / Agents: LLMs, Open-Source Models, Prompt Engineering, RAG, Embeddings, Reranking, Transformers, AI Agents, Agentic & Multi-Agent Workflows.

Frameworks & Evaluation: LangGraph, LangChain, LlamaIndex, Langfuse or equivalent.

Vector Search: Qdrant, FAISS or similar Vector Databases; semantic/hybrid search and retrieval

optimization.

Models & Infrastructure: Ollama, Fine-tuning, LoRA, GPU/CUDA, Model Serving, Inference

Optimization.

Cloud & Platforms: AWS Bedrock, Google Vertex AI / Agent platforms, Azure AI / Agent

platforms, OpenAI platforms, AWS/Azure/GCP.

ML / Computer Vision: CNNs, Ensemble Models, OCR, OpenCV, Face Similarity/Search at Scale,

Image & Document Processing.

Engineering: Strong Python and/or Node.js/TypeScript, REST APIs, Microservices, Docker,

Kubernetes, Distributed Systems, Queues, Databases, Caching, CI/CD, Monitoring and System

Design.

Strong understanding of scalability, high availability, performance, security and cost

optimization for production AI systems.

Preferred candidate profile

79 years of experience in Software Engineering / AI/ML, with significant hands-on experience

building production AI/ML or GenAI systems.

Proven ability to take AI solutions from POC production scale.

Strong system design, architecture and problem-solving skills.

Experience leading technical initiatives and mentoring engineers.

Bachelor's/Master's degree in Computer Science, Engineering, AI/ML, Data Science or related

field preferred.