Codvo
Codvo.ai - Senior AI Engineer
- Compensation
- Not disclosed
- Location
- Pune; Remote; India
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Full time
- Experience
- 10+ years
- Category
- Ai engineering
- Posted
Skills
Full description
About the job :
Employment Type : Full-Time
Location : Remote
About The Role :
We are looking for a Senior AI Engineer with strong full-stack capabilities to join our engineering team.
You will work across multiple client-facing projects that sit at the intersection of AI, data, and webstarting with a live production AI agent platform.
You should be comfortable owning features end-to-end, from LLM pipeline design through to a polished frontend experience.
What You'll Do :
- AI Agent Engineering :
- Design and build AI agent pipelines, including multi-node LangGraph graphs.
- Implement intent routing, multi-turn conversational context, session state management, and tool integrations.
- Develop multi-step reasoning pipelines and graph-based agent workflows.
- RAG & Knowledge Systems :
- Build and maintain Retrieval-Augmented Generation (RAG) systems.
- Design vector search architectures, embedding pipelines, retrieval grounding, and chunking strategies.
- Implement hallucination mitigation techniques and retrieval evaluation frameworks.
- LLM Integration & Optimization :
- Integrate and optimize Large Language Models (LLMs) including OpenAI, Gemini, and Anthropic.
- Develop structured output workflows using JSON schemas.
- Create effective prompt engineering strategies, few-shot examples, and context window management solutions.
- Build provider-neutral client architectures to support multiple LLM vendors.
- Full-Stack Development :
- Design, develop, and deploy end-to-end product features.
- Build scalable FastAPI backends and React/Next.js frontends.
- Implement Server-Sent Events (SSE) streaming and REST API contracts.
- Deliver production-ready UI features independently without requiring dedicated frontend support.
- Observability & Quality :
- Own LLM observability including :
i. Token usage logging
ii. Cost tracking
iii. Fallback detection
iv. Performance monitoring
v. Regression test suites
- Build evaluation pipelines and golden test suites to ensure AI quality and consistency.