Full Stack AI Engineer

About the job :

We're a small, high-output engineering team building AI-powered SaaS products such as RAG systems, agentic workflows, document pipelines, and automation tooling.

You'll work directly with the lead engineer on end-to-end features : designing backend APIs, wiring up LLM integrations, and shipping polished frontends.

This is not a checkbox role - you'll be expected to think architecturally, own your deliverables, and move fast.

Responsibilities :

- Build and iterate on RAG pipelines - chunking strategies, hybrid retrieval, reranking, evaluation.

- Develop agentic workflows using LangChain / LlamaIndex with tool use and memory.

- Ship FastAPI backends with async task queues (Celery Redis) and clean data models.

- Build Next.js / React frontends that are fast and production-ready.

- Integrate with Anthropic, OpenAI, and Gemini APIs - switching models based on cost/task.

- Deploy on Kubernetes (AKS/EKS) or cloud services with proper observability.

- Participate in architecture discussions and code reviews.

Requirements :

- Experience : 5+ Years

- Location : Vizag Office

Required Skills :

- Python, FastAPI, LangChain or LlamaIndex, LLM APIs (OpenAI / Anthropic / Gemini), React / Next.js, TypeScript, PostgreSQL, Docker, REST API design

Preferred Skills :

- Celery Redis, Kubernetes / AKS, Azure / AWS, Terraform, Langfuse / OpenTelemetry, n8n automations, Ollama / local LLMs, Semantic Kernel, Vector DBs (Pinecone, Qdrant, pgvector)

Benefits :

- Strong ownership - you ship things end-to-end without hand-holding.

- Comfortable switching between backend, frontend, and AI layers in the same day.

- You read docs, debug independently, and propose solutions proactively.

- Experience building something from scratch - a side project, open-source tool, anything real.

- Can communicate technical trade-offs clearly to non-technical stakeholders.

- Comfortable in fast-moving, small-team environments with evolving requirements