Generative AI

• Strong Python proficiency with experience in FastAPI, asyncio, modular application design, and parallel processing.
• Familiarity with Python parallel processing modules such as multiprocessing, concurrent.futures, dask for efficient parallel and distributed computing.
• Hands-on experience with GenAI frameworks such as LangChain, LangGraph, and Prompt Engineering.
• Proficient in AWS cloud services and cloud-native architecture.
• Familiar with CI/CD pipelines, Docker, and Kubernetes.
• Familiarity with code quality tools such as pylint, black, isort, mypy, pytest, SonarQube, SonarLint, and Black Duck for linting, formatting, testing, static analysis, and open-source security compliance
• Solid understanding of security best practices in cloud and AI deployments.
• Excellent analytical and communication skills.
• Should be able to network within GenAI team and with other teams as enablement tribe

Key Responsibilities

• Design and implement GenAI solutions using cutting-edge frameworks (e.g.,
• Transformers, LangChain, LangGraph, AWS Bedrock, Agentcore).
• Develop scalable and modular Python applications for deploying generative AI solutions.
• Build and manage cloud infrastructure using AWS services (S3, Lambda, DynamoDB, ECS, EKS).
• Collaborate with data scientists, ML engineers, and product teams to integrate AI models into domain-specific applications.
• Ensure production-grade scalability, reliability, and security of GenAI systems.
• Monitor and optimize system performance using tools like AWS CloudWatch.
• Stay updated with advancements in GenAI, cloud computing, MLOps, and DevOps.
• Contribute to code reviews, documentation, and Python development best practices.

Agentic AI Python LLM NLP