Python GenAI Engineer — Job Update | Vishal Kushwaha
Key Responsibilities & Technical Requirements
Python & Software Engineering
Strong proficiency in Python.
Build production-grade software rather than only notebooks or prototypes.
Develop clean, maintainable, scalable, and reusable code.
Apply software engineering best practices throughout the development lifecycle.
AI Agents & Agentic Frameworks
Build AI agents using frameworks such as:
LangChain
LangGraph
Similar agentic frameworks
Design agent workflows capable of using tools and performing complex tasks.
Explore ways AI agents can augment and automate software development processes.
LLM Fundamentals
Strong understanding of:
Prompt Engineering
Tool / Function Calling
Retrieval-Augmented Generation (RAG)
Embeddings
Context Management
Memory Systems
Large Language Model fundamentals
Architecture
Design modular and platform-agnostic architectures.
Avoid tightly coupling solutions to a single LLM vendor or cloud provider.
Build extensible and reusable AI frameworks and components.
Design solutions that can evolve as AI technologies change.
APIs & Microservices
Design and develop APIs.
Build microservices-based applications.
Develop extensible and reusable frameworks or SDKs.
Integrate AI capabilities into enterprise applications and services.
SDLC & Engineering Practices
Understanding of modern software development lifecycle practices, including:
CI/CD
Git / Version Control
Code Reviews
Software Testing
Automated Development Workflows
The role also involves understanding how AI agents can be used to augment or automate SDLC processes.
AI Evaluation & Observability
Work with AI agent evaluation and observability tools.
Familiarity with:
LangSmith
Tracing frameworks
Custom evaluation harnesses
Monitor and evaluate agent behavior and application performance.
AI Governance & Responsible AI
Strong understanding of AI governance concepts, including:
Guardrails
Access Control
Auditability
Human Oversight
Responsible AI practices