Senior Full Stack Engineer - Agentic AI Systems

Company : Soulpage IT Solutions Pvt. Ltd.

Location : Hyderabad - on-site

Experience : 5 - 9 years

About the Role :

• Soulpage is an AI-first technology company building enterprise AI products and platforms for clients including Fortune 500 and government organizations, alongside our own SaaS products.

• You will join a dedicated pod (engineers + BA + Delivery Lead + Solution Architect) working directly with the CTO office. This is product engineering with ownership - not ticket execution : you will take modules from architecture through production, working in the prod repositories to enterprise standards.

What You Will Do :

• Design and build backend services and APIs (Python) that productionise AI/ML and agentic workflows - from prototype-grade pipelines to reliable, observable, scalable services.

• Build and orchestrate agentic systems : multi-step LLM workflows, tool/function calling, retrieval pipelines, evaluation and guardrails.

• Work with graph and document data models - entity extraction outputs, knowledge-graph queries, large-scale document processing pipelines.

• Contribute across the stack where needed : React-based front ends for internal tools, review dashboards, and co-pilot interfaces.

• Own modules end to end : architecture proposals, milestone delivery with exit criteria, demos to all stakeholders, documentation as a first-class deliverable.

• Participate in fortnightly demos and architecture discussions with the engineering leadership.

Must-Have Skills :

• 5+ years of backend engineering with Python (FastAPI/Flask/Django), including REST/gRPC API design, async processing, and message queues.

• Hands-on production experience with LLM-based and agentic systems : at least one of LangChain/LangGraph, CrewAI, AutoGen, OpenAI/Anthropic SDKs with tool calling, or equivalent in-house frameworks - beyond tutorials : you have shipped and debugged these in production.

• RAG pipelines : chunking/embedding strategies, vector databases (pgvector, Pinecone, Qdrant, or similar), retrieval quality evaluation.

• Solid relational database skills (PostgreSQL) plus exposure to at least one NoSQL or graph store.

• Cloud-native development on AWS or Azure : containers (Docker), CI/CD, infrastructure basics; Kubernetes exposure preferred.

• Engineering rigor : automated testing, code review discipline, observability (logging/metrics/tracing).

• Strong written and spoken communication.