- Experience
- 1 – 3 years
- Pay
- Not disclosed
- Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
- Location
- Pune, India
- Work mode
- On-site
- Job type
- Full-time
About this role
AppZen provides AI-powered spend-to-pay software used by large enterprises for invoice, expense, and card processing. This role builds and ships LLM-powered and agentic features that extract, validate, and decide on financial documents in production.
What you will do
- Build and improve LLM-powered features and multi-step agentic workflows for invoices, receipts, and expenses
- Build RAG pipelines (chunking, embeddings, vector search, re-ranking) for accurate financial decisions
- Implement function calling and API integrations for structured JSON outputs
- Build evaluation datasets, metrics, and automated test suites for accuracy, latency, and cost
- Package and deploy models/services with Docker and CI/CD, add monitoring and logging
- Collaborate with senior engineers, data scientists, and product managers on requirements and design
What the employer expects
- 1–3 years building and deploying ML/AI solutions in production, including at least 1 year on LLM applications
- Strong Python skills and experience building REST APIs (FastAPI or Flask)
- Hands-on experience with LangChain, LangGraph, LlamaIndex or similar and major LLM APIs
- Practical experience building RAG pipelines with vector databases
- Solid ML/NLP fundamentals and working experience with PyTorch or similar
- Working knowledge of Docker, Git, CI/CD, and cloud deployment (AWS/GCP/Azure)
Skills
- Python
- LangChain
- LangGraph
- LlamaIndex
- RAG
- vector databases
- Pinecone
- Milvus
- pgvector
- FAISS
- FastAPI
- Flask
- PyTorch
- Docker
- CI/CD
Apply on the employer's site
The application opens on Lever. Dev Portal Notes does not collect your application or charge a fee.
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