Software Engineer – AI (Backend)

About the job:
We’re hiring a Software Engineer – AI (Backend) to build and ship production backend and AI systems across real client and internal use cases. You’ll design APIs and services, build LLM-powered applications, and own them in production.
This is a full-time, work-from-office role in Hyderabad.
About us:
We’re a new age tech & business services company, HQ’ed in Hyderabad with clients across the world. Find out more at https://www.linkedin.com/company/gitforce
What You’ll Do
TL;DR: Build and run the backend and AI systems behind real products.
Design and build backend services and APIs in Python (FastAPI, Flask, or similar)
Design data models and work with SQL and PostgreSQL
Build AI-powered applications using LLM APIs (OpenAI, Anthropic, Google, and open-source models)
Build RAG pipelines using embeddings, retrieval, reranking, and vector databases
Develop AI agents, tool-calling workflows, and multi-step LLM systems
Integrate with third-party APIs, databases, and services
Deploy, monitor, debug, and improve systems in production
Work closely with product, founders, and client teams to turn requirements into technical solutions
Qualifications
TL;DR: Strong backend engineering fundamentals in Python, plus hands-on experience building AI-powered applications.
You Are:
2 to 5 years into your professional engineering career
A strong backend engineer who has built and shipped AI-powered features
Someone who cares about reliable, well-tested production systems
Comfortable picking up new frameworks and tools quickly
Someone who enjoys owning a system end to end, not just isolated tickets
Must-haves:
Strong Python, with experience building production backend services and APIs
Solid SQL and PostgreSQL, including schema design
Hands-on experience with LLM APIs, including prompt engineering, structured outputs, and tool calling
Experience building RAG pipelines or AI agents (LangChain, LlamaIndex, LangGraph, or similar)
Good grasp of API design, software architecture, Git, testing, and production engineering fundamentals
Strong problem-solving and communication skills
Nice-to-haves:
Vector databases: Pinecone, pgvector, Weaviate, Qdrant, Chroma, or similar
LLM evaluation, observability, tracing, or monitoring
Redis, queues, async processing, or distributed systems
Docker, CI/CD, and cloud (AWS, GCP, or Azure)
Some frontend experience (React, Next.js, TypeScript)

Work arrangement
No