Graduate Engineer

About the Role

We are looking for an experienced GenAI / AI Engineer to design and develop scalable AI applications and integrate LLM-based capabilities into enterprise solutions.

Key Responsibilities

• Design and develop GenAI/LLM-based applications using Python.
• Build and implement Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases.
• Develop AI workflows and agentic applications using LangChain and LangGraph.
• Design and implement vector search and semantic retrieval using PostgreSQL and PGVector.
• Work with LLMs, embeddings, prompt engineering, document processing, and context retrieval.
• Develop scalable and production-ready AI services and APIs using Python.
• Deploy and integrate AI applications with AWS cloud services.
• Optimize RAG pipelines for accuracy, relevance, latency, and scalability.
• Work closely with product, engineering, and data teams to translate business requirements into AI solutions.
• Write clean, maintainable, testable, and well-documented code.
• Troubleshoot performance, integration, and production issues related to AI applications.

Requirements & Tech Stack

• 5+ years of software development experience.
• Strong hands-on experience with Python.
• Strong experience with PostgreSQL.
• Hands-on experience with PGVector / vector databases.
• Strong understanding and implementation experience of RAG (Retrieval-Augmented Generation).
• Hands-on experience with LangChain.
• Hands-on experience with LangGraph.
• Good experience with AWS and cloud-based application deployment.
• Understanding of LLMs, embeddings, vector search, prompt engineering, and AI application architecture.

Good to Have

• Experience building AI agents / agentic workflows.
• Experience with REST APIs and microservices.
• Knowledge of Docker/Kubernetes.
• Experience with AWS services such as S3, Lambda, ECS/EKS, Bedrock, OpenSearch, and RDS.
• Experience with CI/CD and production deployment of AI applications.
• Experience working with enterprise GenAI solutions.

Qualifications

The ideal candidate is a strong hands-on engineer with proven experience building and deploying production-grade GenAI applications using RAG, LangChain, LangGraph, PostgreSQL/PGVector, and AWS.