Website:
cittaai.com
Job details:
About the job
Job Title: Senior AI Engineer
Experience: 6+ Years
Location: Hyderabad, India
Employment Type: Full-time
Role Summary
Senior AI Engineer who takes LLM-backed features from architecture to production and keeps them healthy — RAG pipelines, agent systems, the Python services behind them, and the evaluation and observability that prove they work. Senior IC scope: you own the design, make the trade-offs between quality, latency, scale, and cost, and set patterns other engineers build on.
Responsibilities
- Design and ship enterprise AI applications: copilots, knowledge assistants, and agentic workflows.
- Build RAG pipelines end to end — ingestion, chunking, embeddings, hybrid search, reranking, and context construction.
- Develop agent systems with tool calling, state, memory, human-in-the-loop controls, and failure recovery.
- Build the backend services and APIs behind them in Python and FastAPI, and the interfaces in React or Next.js.
- Define evaluation for groundedness, relevance, latency, reliability, and cost — not manual spot checks.
- Own deployment and operations: CI/CD, containers, cloud, observability, and incident response.
- Apply AI security and governance — auth/authz, prompt injection defense, sensitive-data handling, audibility.
- Lead design and code reviews, mentor engineers, and build reusable patterns.
Required Skills
- 6+ years in software or AI engineering, with production Generative AI applications you can walk us through.
- Strong Python, plus REST APIs, FastAPI, and distributed application architecture.
- Hands-on depth in LLMs, RAG, embeddings, agents, and tool calling.
- LangChain, LangGraph, or an equivalent orchestration framework.
- Vector databases and semantic or hybrid search.
- Cloud-native: Git, CI/CD, containers, automated testing, and debugging live systems.
Nice to have
- Production frontend with React and/or Next.js.
- Azure OpenAI / Bedrock / Vertex AI.
- Azure AI Search, Pinecone, Weaviate, or pgvector.
- LLMOps and evaluation tooling · observability platforms.
- Kubernetes, Docker, Helm, Terraform · Azure DevOps or GitHub Actions.
- OAuth2, OIDC, Entra ID, RBAC.
We are not looking for someone who is
- Stopping at the demo — prototypes that impress in a meeting but were never load-tested, evaluated, or handed to real users.
- Treating prompt tuning as the whole engineering job.
- Waiting for fully specified requirements; turning ambiguity into a shippable design is the work.
- Shipping without measurement — we expect evaluation harnesses and telemetry, not vibes.
- Uninterested in what happens after deploy: incidents, cost, latency, and drift are part of the role.
- Building alone — design reviews, code reviews, and mentoring are how the work compounds here.
Skills:
- Python · FastAPI · React · LangGraph · RAG · AI Agents · Vector Databases · LLM Evaluation
- Docker · Kubernetes · Azure · LLMOps · Observability
Click on Apply to know more.
