AI Native Software Engineer

Project Role : AI Native Software Engineer
Project Role Description : Build and ship production-ready software using AI as a core part of the engineering lifecycle. Apply AI-native practices to develop and validate solutions, maintain quality and compliance, and continuously improve how software is built and operated.
Must have skills : Python (Programming Language)
Good to have skills : Agentic Design
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education
Role Summary Build and deploy production-grade AI applications using LLMs, RAG pipelines, and agentic systems Work across backend (Python/FastAPI) and frontend (React/JavaScript) stacks Deploy and operate AI services in cloud-native Kubernetes environment Leverage modern GenAI frameworks and tooling to accelerate development Key Responsibilities Design and develop LLM-powered backend services using Python and FastAPI Build Retrieval-Augmented Generation (RAG) pipelines using vector databases Implement agentic workflows using frameworks such as AutoGen or similar Design and expose RESTful APIs following OpenAPI / REST API specifications Integrate backend AI services with React + JavaScript frontend applications Deploy, manage, and scale AI services on Kubernetes Use LangChain to orchestrate prompts, tools, chains, memory, and agents Use LangSmith for: Prompt/version tracking LLM tracing and debugging Evaluation and performance monitoring Apply prompt engineering best practices and maintain reusable prompt libraries Collaborate with cross-functional teams to deliver end-to-end AI solutions Ensure security, reliability, observability, and performance of AI systems Required Technical Skills Backend & APIs Strong hands-on experience with: Python FastAPI Experience designing and consuming RESTful APIs Familiarity with OpenAPI / Swagger specifications Frontend Working knowledge of: React JavaScript Experience integrating frontend applications with backend APIs Generative AI & LLMs Hands-on experience working with Large Language Models (LLMs) Agentic system design patterns knowledge Experience building RAG-based applications Knowledge of: Embeddings Vector search Context management Practical experience with prompt engineering GenAI/Agentic Frameworks & Tooling (Must Have) LangChain Chains, tools, agents, memory LangSmith Prompt tracing, debugging, evaluation, and monitoring Agentic frameworks AutoGen or similar Experience with multi-agent orchestration, tool-calling agents, planners, and executors Protocols like MCP / A2A Cloud & DevOps Experience with: Docker Kubernetes Understanding of cloud setup and deployment (AWS / Azure / GCP) Basic CI/CD knowledge is a plus Gen AI Tools AI productivity tools for general development: GitHub Copilot Claude / Cursor / Cline or similar Good to Have/Differentiators Working knowledge/experience with Vector databases: Pinecone, FAISS, Weaviate, Chroma, or equivalent Graph databases: Apache AGE, Neo4j etc. Strong basics in Security/AuthN/AuthZ: JWT, OAuth2 Working knowledge of monitoring and observability tools. Soft Skills Strong problem-solving and debugging skills Ability to work independently and take ownership Clear communication and collaboration skills High curiosity for fast-evolving AI and GenAI ecosystems