Python Developer — AI & Data

Role Overview

We're looking for a Python Developer who has built AI workflows end to end and understands what separates a working demo from a production system: retrieval that returns the right context, guardrails that hold, evaluation that tells you whether a change helped or hurt, and pipelines that stay reliable at volume. This role sits at the centre of our AI-assisted automation and scaling efforts.

Responsibilities

• Design, build, and operate AI workflows in Python, from prototype through to production
• Build RAG (Retrieval-Augmented Generation) pipelines — chunking, embeddings, vector search, retrieval quality, and context management
• Implement guardrails and safety controls around LLM outputs: input/output validation, grounding, hallucination mitigation, prompt-injection defence, and fallback behaviour
• Build evaluation harnesses that measure output quality objectively
• Build AI-driven automation that removes repetitive manual work, and scale it reliably as usage grows
• Integrate LLMs and ML models into production: API endpoints, inference services, orchestration, and supporting pipelines
• Work with AI orchestration and agent frameworks, and integrate with external tools and services
• Instrument AI systems for observability — token usage, latency, cost, failure modes, and output quality over time
• Collaborate with data scientists and ML engineers to take models from notebook to production
• Work with data science and data engineering tools like Pandas, NumPy, and Jupyter for data manipulation, analysis, and validation

Requirements

• 3+ years of backend development experience in Python
• Hands-on AI workflow experience
• Strong command of Python and at least one Python web framework (FastAPI, Django, or Flask)
• Familiarity with MySQL and BigQuery, including schema design and query optimization
• Working knowledge of core AI engineering concepts: RAG, embeddings, vector databases, guardrails, context management, and evaluation
• Hands-on experience with AI tools and frameworks — LLM APIs, orchestration frameworks (LangChain, LlamaIndex, or similar), and vector stores
• Experience building AI-assisted automation and scaling it beyond a proof of concept
• Solid understanding of RESTful APIs, HTTP, JSON, and integration with external services
• Experience implementing authentication, authorization, and security best practices
• B.E. / B.Tech / MCA or equivalent

Nice to Have

• Experience with Docker or containerized deployments
• Experience with local / open-source LLMs — running, optimizing, or integrating models such as LLaMA, Mistral, or Gemma using serving tools like Ollama or vLLM

Benefits

• Health insurance
• Provident Fund

Skills

• Python
• FastAPI
• LangChain
• RAG
• MySQL