GenAI Technical Lead

GenAI Technical Lead
Experience Level: Minimum 7-10 years of total IT experience (at least 2+ years in Generative AI, LLMs, or related AI/ML technologies)
Should have strong technical expertise in Python, hands-on experience with at least one GenAI framework (LangGraph, LangChain, or Google AI Development Kit), and strong working knowledge of one hyperscaler platform (Google Cloud, Azure, or AWS).
The associate should lead solution design, integrating LLMs into enterprise workflows, mentoring team members, and driving production-grade implementation of GenAI use cases.
Good knowledge of MLOps or DevOps teams to automate model deployment, versioning, and monitoring.
Key Responsibilities:
1. Solution Design
Design, architect, and implement Generative AI workflows and agents using frameworks such as LangChain, LangGraph, or Google ADK.
Integrate LLMs (e.g., Llama, Gemini, GPT, Claude) into enterprise systems and custom applications.
Define and implement retrieval-augmented generation (RAG) pipelines using vector databases (e.g., ChromaDB, Pinecone, FAISS, Weaviate, Vertex AI Matching Engine).
Architect scalable and secure GenAI microservices leveraging cloud-native components.
2. Development & Implementation
Lead Python-based development efforts for building prompt orchestration, tool agents, and data pipelines.
Develop and deploy APIs or microservices integrating LLMs with enterprise data sources.
Implement prompt optimization, context management, and model performance tuning.
3. Cloud Integration
Architect, deploy, and monitor GenAI workloads on one hyperscaler:
GCP (Vertex AI, Document AI, AlloyDB, BigQuery, Cloud Run)
Azure (OpenAI Service, Cognitive Search, Azure ML)
AWS (Bedrock, SageMaker, Lambda, API Gateway)
Manage cloud infrastructure for scaling AI models, ensuring cost efficiency and compliance.

Work arrangement
No