We are seeking a highly skilled Senior GenAI Backend Engineer with 8+ years of backend engineering experience and solid expertise in designing, building, and deploying enterprise-grade Generative AI and Agentic AI solutions.

The ideal candidate should have deep experience in developing scalable AI platforms, autonomous AI agents, Retrieval-Augmented Generation (RAG) systems, LLM integrations, and distributed backend architectures. This role requires hands-on engineering expertise along with technical leadership in designing AI-native enterprise applications.

Requirements

Key Responsibilities

AI Platform Development

- Design, develop, and deploy enterprise-grade GenAI applications using Large Language Models (LLMs).
- Build intelligent AI agents using Agentic AI frameworks and multi-agent orchestration.
- Develop scalable Retrieval-Augmented Generation (RAG) solutions using Vector Databases and Knowledge Graphs.
- Design Graph RAG, Hybrid RAG, and semantic retrieval pipelines.
- Integrate OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or other foundation models into enterprise applications.

Backend Engineering

- Design high-performance REST APIs and microservices using Python.
- Build distributed backend systems capable of handling high-volume concurrent workloads.
- Develop secure multi-tenant architectures.
- Design event-driven systems using asynchronous programming patterns.
- Optimize API performance, scalability, and latency.

AI Agent Development

- Develop autonomous AI workflows using:
- LangGraph
- LangChain
- Semantic Kernel
- DSPy
- Model Context Protocol (MCP)
- Agent-to-Agent (A2A) communication
- Build reusable AI tools, planners, memory systems,



and orchestration pipelines.

System Architecture

- Define backend architecture for AI-native applications.
- Design scalable cloud-native systems on AWS, Azure, or GCP.
- Implement observability, monitoring, logging, and tracing for AI workloads.
- Design secure APIs with authentication, authorization, and data protection.

Collaboration & Leadership

- Lead backend engineering initiatives for AI projects.
- Mentor junior developers and AI engineers.
- Collaborate with Product Managers, Architects, Data Scientists, and DevOps teams.
- Participate in architecture reviews and technical decision-making.
- Drive engineering best practices, coding standards, and design reviews.

Required Technical Skills

Programming

- Python (Expert)
- JavaScript / TypeScript
- SQL
- NoSQL databases

Backend Frameworks

- FastAPI
- Django
- Flask

AI & LLM Frameworks

- LangChain
- LangGraph
- Semantic Kernel
- DSPy
- OpenAI SDK
- Azure OpenAI
- Anthropic Claude APIs
- Google Gemini APIs

Agentic AI

- Multi-Agent Systems
- Agentic Orchestration
- Model Context Protocol (MCP)
- Agent-to-Agent (A2A) Communication
- AI Planning & Tool Calling
- Prompt Engineering
- Function Calling

RAG Technologies

- Vector Databases (Qdrant, Pinecone, Milvus, Weaviate, ChromaDB)
- Hybrid Search
- Graph RAG
- Semantic Search
- Embedding Models
- Knowledge Graphs

Databases

- PostgreSQL
- MongoDB
- Redis
- Elasticsearch

Cloud & DevOps

- Docker
- Kubernetes
- GitHub Actions / Azure DevOps / GitLab CI
- Terraform (preferred)
- Azure / AWS / GCP

API Development

- REST APIs
- WebSockets
- Async Programming
- OAuth2 / JWT
- API Gateway

Work Location: In person

📌 Lead Python - Gen AI Developer (Thiruvananthapuram)
🏢 PIT Solutions
📍 Thiruvananthapuram