GenAI Engineer

Skill List

Claude code, LangGraph, agentic AI, architectural engineering, artificial intelligence, automatic programming, building and public works, cabling, civil engineering, electrical engineering, engineering, generative AI, information technology, programming, software devel

Min 10+ years of experience in Python/Microservices development.
Experienced professional with strong Python development and Generative AI expertise, especially in prompt engineering.

Leverage GenAI to accelerate:
Requirement gathering and analysis.
Design creation (HLD/LLD).
Reverse engineering of existing applications.
Development for enterprise-scale projects.
Lead and enable development teams to effectively use GenAI tools and frameworks.
Reverse engineer application codebases (Python, Java, Angular, Mule) to auto-generate:
Architecture diagrams.
Data flow and sequence diagrams.
Accelerate design creation using GenAI:
Propose API specifications.
Apply Domain-Driven Design (DDD) patterns.
Utilize Claude Code, GitHub Copilot, and similar tools for:
Pull Request reviews.
Automated test generation.
Development, Code refactoring and optimization.
Build and deploy AI agents using LangChain, LangGraph, integrated with enterprise APIs.
Implement RAG (Retrieval-Augmented Generation) pipelines for knowledge-driven applications.
Drive prompt engineering best practices and GenAI use case adoption across teams.
Conduct workshops and training sessions for developers on GenAI tools and frameworks.
Ensure security, compliance, and responsible AI usage in all GenAI implementations.

Must-Have Skills:
Strong proficiency in Python and microservice development.
Hands-on experience with Claude Code, GitHub Copilot, and prompt engineering.
Expertise in LangChain, LangGraph, LangFlow, and agent-based architectures.
Solid understanding of software design principles, DDD, and cloud-native architectures.
Experience building AI solutions integrated with enterprise APIs.

Preferred Skills:
Familiarity with AWS services (Bedrock, Lambda, S3, DynamoDB, Postgres/PGVector).
Knowledge of containerization (Docker) and CI/CD pipelines.
Experience with vector databases, embedding models, and LLM fine-tuning.
Understanding of AI governance, bias mitigation, and responsible AI frameworks.
Proficiency with FastAPI, LangChain, LangGraph, Bedrock, Anthropic APIs.
Experience with observability tools for AI workflows.

Soft Skills:
Strong leadership and mentoring abilities.
Excellent communication and collaboration skills.
Ability to drive innovation and evangelize GenAI adoption across teams