Job Overview This role focused on building and operating multi-agent AI applications, RAG systems, and production workflows. The engineer owns features end-to-end - from agent design and retrieval pipelines to APIs, UI, and deployment - in a Dockerized, enterprise product setting.

Key Responsibilities

- Design, build, and iterate on multi-agent systems (orchestration, tool calling, memory, handoffs, evaluation).
- Build and improve RAG pipelines: ingestion, chunking, embeddings, hybrid search, reranking, grounding, and citation quality.
- Implement workflow engines for long-running business processes (state machines, async jobs, retries, human-in-the-loop).
- Develop backend services in Python (APIs, services, background workers).
- Build frontend experiences that present agent/workflow results clearly (status, audit trails, approvals).
- Own DevOps for these systems: containers, CI/CD, secrets, observability, and cost/latency controls.
- Work with product and domain experts to turn ambiguous requirements into reliable agent behavior.
- Write tests, evals, and runbooks so agent systems stay shippable in production.

Qualifications & Requirements Core Requirements:

- Experience: 4–7+ years of professional software engineering experience, with dedicated hands-on experience building and shipping AI applications.
- Education: Bachelor's degree in Computer Science, Engineering, or equivalent practical experience, backed by a portfolio of shipped multi-agent or RAG projects.
- Backend: Strong production experience with Python,



including REST/GraphQL APIs, microservices, and async/background workers (Celery/Redis task queues).
- Multi-Agent Systems: Hands-on experience with agent frameworks (e.g., LangGraph, LangChain), tool calling, and multi-agent orchestration patterns.
- RAG Applications: Proven experience with vector search, embeddings, retrieval quality, context design, hallucination mitigation, vector databases (pgvector, OpenSearch, Pinecone, Weaviate), and guardrails.
- Full-Stack Development: Hands-on proficiency with Django / Django REST Framework, Flask, and modern React / Next.js with TypeScript.
- Debugging & Observability: Proven ability to trace agent execution, resolve retrieval misses, fix workflow stuck states, and troubleshoot production incidents.

Nice To Have

- Prior exposure to pharmaceutical operations, procurement, or trade distribution workflows.
- Working knowledge of pharma supply chain management, batch tracking, or commercial inquiry processing.
- Understanding of pharmaceutical quality assurance (QA) and quality control (QC) operational procedures.

Application Process 1

Submit Application

Complete the application form below with your details and CV

2

Initial Screening

Our HR team will review your application and contact suitable candidates

3

Technical Interview

Selected candidates will have a technical interview with the department head

4

Final Discussion

Final round with senior leadership team and offer discussion

📌 Senior Full-Stack AI Engineer (Hyderabad)
🏢 HRV Pharma
📍 Hyderabad