Job Summary:

We are looking for an experienced AI / GenAI Software Engineer with 5+ years of software engineering experience and strong expertise in Generative AI, NLP, Large Language Models (LLMs), Information Retrieval and RAG architectures.

The ideal candidate will have a strong production engineering mindset and experience taking AI solutions from experimentation to reliable, scalable enterprise applications.

Key Responsibilities:

- Design, develop and maintain production-grade AI/GenAI applications using Python.

- Develop enterprise solutions using LLMs, NLP, Prompt Engineering and Retrieval Augmented Generation (RAG).

- Design and implement RAG, hybrid retrieval and GraphRAG architectures.

- Work with vector search and information retrieval technologies, including OpenSearch or similar platforms.

- Develop APIs and AI services using modern Python frameworks and practices.

- Build automated AI evaluation pipelines to measure retrieval quality and LLM output quality.

- Write clean, maintainable and typed Python code using modern Python features.

- Develop comprehensive automated tests using pytest, mocking and unit/integration testing.

- Follow software engineering best practices including Git, merge requests, code reviews, CI/CD and code quality checks.

- Containerize and manage applications using Docker.

- Work across the SDLC and CRISP-DM lifecycle, converting AI experiments into deterministic and production-ready software.

- Collaborate with technical and non-technical stakeholders to understand requirements and deliver practical AI solutions.

- Continuously evaluate emerging GenAI technologies and identify opportunities for business/product improvement.

Mandatory Skills:

- 5+ years of professional software engineering experience

- Strong hands-on experience with Python

- Strong experience in Generative AI / LLMs

- Experience with NLP / Information Retrieval

- Hands-on experience with RAG

- Experience with Vector Search / Semantic Search

- Experience with Hybrid Retrieval

- Strong understanding of Prompt Engineering

- Experience developing production-grade AI applications

- Experience with pytest / automated testing

- Experience with Git, code reviews and software development lifecycle

- Experience with Docker / containerization

Preferred Skills:

- GraphRAG

- OpenSearch

- Pydantic

- Async Python / async-await

- FastAPI

- Automated LLM/RAG evaluation

- RAGAS / DeepEval / LangSmith or similar evaluation frameworks

- AWS Bedrock

- Azure OpenAI

- Model Context Protocol (MCP)

- Knowledge Graphs / Neo4j

Candidate Profile:

We are looking for someone who:

- Has a strong hands-on engineering mindset

- Can build AI solutions beyond prototypes and notebooks

- Understands how to take an AI experiment into production

- Has strong analytical and problem-solving abilities

- Can explain complex AI concepts to technical and non-technical stakeholders

- Learns quickly and adapts to the rapidly evolving GenAI ecosystem

- Takes ownership and works proactively

- Focuses on practical, scalable and reliable solutions

Important:

Candidates with only basic Python, generic Machine Learning, Data Science, Prompt Engineering or simple Chatbot experience may not be suitable.

Strong hands-on experience in RAG + LLM/GenAI + Python + production software engineering is highly preferred.