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 :

- Lead end-to-end design and development of GenAI-powered applications.

- Ability to understand and translate customer requirement into scalable AI architectures and meaningful design leveraging cloud services.

- Drive adoption of LLM orchestration frameworks (LangChain 1.0, LangGraph, OpenAI tools, custom agents).

- Keep pace with technological evolution in Gen AI space, explore and set up PoC for better solutions.

2. Generative AI Development :

- Build RAG pipelines using vector databases, embeddings, and document indexing.

- Design and implement Agentic workflows.

- Implement vector search using PGVector, FAISS etc.

- Create embedding pipelines, chunking strategies, metadata tagging, and retrieval optimizations, MCP.

3. Python & Cloud :

- Build backend services, API layers, and model-serving components in Python (Flask).

- Understanding of AWS services such as ECS, API Gateway, S3, Bedrock, CloudWatch, SageMaker.

- Performance and Security as first principles.

4. Collaboration :

- Lead a small team of engineers, conduct code reviews and design reviews.

- Work with cross-functional teams Product, Architecture, Security, Data Engineering.

- 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

- Cloud - AWS - ECS

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

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