Lead Engineer

Role Overview
We are looking for an experienced Lead Engineer (8 - 10 Years) with strong expertise in Python, AWS Cloud, Generative AI, and hands-on experience in RAG (Retrieval Augmented Generation), Agentic workflows, and building LLM-powered applications.
The ideal candidate will lead design, architecture, and development of scalable AI solutions, mentor the team, and collaborate closely with product and architecture teams.

Key Responsibilities:

1. Architecture, Design & Technical Leadership
   a. Lead end-to-end design and development of GenAI-powered applications.
   b. Ability to understand and translate customer requirement into scalable AI architectures and meaningful design leveraging cloud services
   c. Drive adoption of LLM orchestration frameworks (LangChain 1.0, LangGraph, OpenAI tools, custom agents).
   d. Keep pace with technological evolution in Gen AI space, explore and set up PoC for better solutions
2. Generative AI Development
   a. Build RAG pipelines using vector databases, embeddings, and document indexing.
   b. Design and implement Agentic workflows
   c. Implement vector search using PGVector, FAISS etc.
   d. Create embedding pipelines, chunking strategies, metadata tagging, and retrieval optimizations.
   e. MCP
3. Python & Cloud
   a. Build backend services, API layers, and model-serving components in Python (Flask).
   b. Understanding of AWS services such as ECS, API Gateway, S3, Bedrock, CloudWatch, SageMaker.
   c. Performance and Security as first principles
4. Collaboration
   a. Lead a small team of engineers, conduct code reviews and design reviews.
   b. Work with cross-functional teams Product, Architecture, Security, Data Engineering.
   c. Ensure best practices in coding, testing, observability, and DevOps.
   Required Skills:

• Strong proficiency in Python (Flask, REST, async programming).
• Deep hands-on experience with Generative AI and LLM-based applications.
• Expertise in RAG development, embeddings, vector databases.
• Experience with Agent frameworks (LangChain 1.0, LangGraph, ReAct, OpenAI Assistants, or custom agents).
• Strong understanding of AWS/Azure/GCP Cloud architecture.
• Experience with API development, microservices, and event-driven systems.
• Familiarity with CI/CD pipelines, Docker, GitLab/GitHub Actions.

Mandatory Competencies

Data Science and Machine Learning - Data Science and Machine Learning - Gen AI

Programming Language - Python - Flask

Beh - Communication

DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - GitLab,Github, Bitbucket

Cloud - AWS - AWS S3, S3 glacier, AWS EBS

Data Science and Machine Learning - Data Science and Machine Learning - AWS Sagemaker

Cloud - AWS - ECS

Development Tools and Management - Development Tools and Management - CI/CD