- Design, build, and deploy end -to -end AI/ML systems with a focus on real -world applications

- Develop and optimise LLM -powered applications, including chat systems, copilots, and agent -based workflows

- Build scalable APIs and backend systems to serve AI models in production

- Work on retrieval -augmented generation (RAG) pipelines and vector search systems

- Collaborate with cross -functional teams (product, design, data) to deliver features rapidly

- Ensure production readiness through proper testing, monitoring, and optimisation

- Mentor junior engineers and contribute to team knowledge sharing

- Continuously explore and integrate emerging AI tools, frameworks, and best practices


Requirements
- Experience

- 2–3 years of experience in AI/ML + Software Engineering roles





- Programming & Engineering

- Strong proficiency in Python

- Understanding of system design

- Experience building REST APIs / microservices

- MLOps & Infrastructure Experience with:

- Docker (containerization)

- Kubernetes (deployment & scaling)

- CI/CD pipelines for ML systems

- Familiarity with cloud platforms (AWS / GCP / Azure)

- AI / ML & LLM Stack Hands -on experience with:

- LLMs & GenAI Prompt engineering, fine -tuning basics

- Frameworks & Libraries like LangChain / LlamaIndex

- Hugging Face, PyTorch ecosystem

- Retrieval & Search FAISS or other Vector Databases (Pinecone, Weaviate, Chroma, etc.)

- Agentic AI Systems, multi -agent workflows, MCP or similar

- Preferred Experience

- Experience with document parsing & processing pipelines (e.g., PDFs, tables, OCR, structured extraction)

- Exposure to knowledge graphs or hybrid retrieval systems

- Familiarity with UI frameworks (StreamLit)