Software Engineer (AI)
Mid-level AI engineer (3–4 yrs) building enterprise generative-AI applications on Python/FastAPI backends: LLM API integrations (OpenAI, Azure OpenAI, Anthropic, Gemini), RAG pipelines with embeddings and vector databases, prompt engineering, and AI-agent workflows, under guidance of a senior AI engineer and architect in Ahmedabad.
- Compensation
- Not disclosed
- Location
- Ahmedabad , GJ, India
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 3–4 years of software engineering experience
- Strong hands-on Python experience
- FastAPI
- REST API development and backend application experience
- Understanding of API authentication, error handling, and integration
- Understanding of Generative AI and LLMs
- Experience working with LLM APIs
- Prompt engineering
- Understanding of tokens, context windows, temperature, embeddings
- Experience with one or more LLM providers (OpenAI, Azure OpenAI, Anthropic, Google Gemini)
- Practical experience with Retrieval-Augmented Generation (RAG)
- Embeddings and semantic search
- Vector databases
- Document ingestion and chunking
- Basic understanding of RAG quality and hallucination issues
- PostgreSQL
- Git / GitHub / Azure Repos
- Docker
- Basic Azure or AWS experience
Nice to have
- LangChain
- LangGraph
- Neo4j / GraphRAG
- Model Context Protocol (MCP)
- Ollama / open-source LLMs
- Azure OpenAI
- React / Next.js
- Redis
- CI/CD with Azure DevOps / GitHub Actions
- Basic understanding of LLM evaluation and AI guardrails
Full description
Role Overview
We are looking for an AI Engineer — GenAI, RAG & Backend with 3–4 years of software engineering experience and hands-on exposure to Generative AI, LLM applications, RAG, APIs, and AI-agent workflows.
The candidate will work closely with the Senior AI/ML Engineer and AI Architect to develop, integrate, test, and deploy enterprise-grade AI applications.
The ideal candidate should have a strong foundation in Python backend development and practical knowledge of modern GenAI technologies.
Key Responsibilities
- Develop and maintain Generative AI applications using Python and LLM APIs.
- Build and enhance RAG pipelines using embeddings, vector databases, retrieval, and contextual generation.
- Develop backend services and APIs using Python, FastAPI, and REST APIs.
- Integrate LLM providers such as OpenAI, Azure OpenAI, Anthropic, and Gemini.
- Implement prompt engineering techniques for reliable and consistent LLM responses.
- Develop basic AI-agent and tool-calling workflows under the guidance of senior engineers.
- Work with vector databases for semantic search and knowledge retrieval.
- Design and implement database integrations using PostgreSQL.
- Write reusable, maintainable, and well-tested Python code.
- Containerize applications using Docker and support cloud deployment.
- Troubleshoot API, LLM, RAG, and application-level issues.
- Participate in code reviews, technical discussions, testing, and documentation.
- Work with the Senior Engineer and AI Architect to implement technical designs and AI workflows.
- Perform POCs and evaluate new GenAI technologies when required.
- Monitor and improve application performance, reliability, response quality, and LLM usage costs.
Must-Have Skills
Programming & Backend
- Python — strong hands-on experience
- FastAPI
- REST API development
- Experience developing backend applications
- Understanding of API authentication, error handling, and integration
Generative AI & LLM
- Understanding of Generative AI and LLMs
- Experience working with LLM APIs
- Prompt engineering
- Understanding of tokens, context windows, temperature, embeddings, etc.
- Experience with one or more LLM providers such as:
- OpenAI