Junior AI Engineer - Mumbai
ClanX (company site, opens in a new tab)2+ yrsMumbaiOn-siteDirect career pageEst. 10–18 LPA
Posted 16h ago
Reach people at ClanX
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at ClanX you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Develop and own LLM-powered chat, content understanding, and recommendation features using NestJS and TypeScript backend.
- Manage orchestration, tool calling, memory, and evaluation for AI agents and multi-step pipelines to ensure reliability.
- Build and optimize RAG systems with embeddings and databases like Qdrant, Elasticsearch, and MongoDB; improve production through streaming, caching, and scalable processing.
Minimum Requirements
- Minimum 2 years software engineering experience with strong TypeScript and Node.js skills; NestJS experience preferred.
- Experience shipping at least one LLM-powered production feature (assistant, RAG system, or content extraction pipeline).
- Hands-on with Gemini, OpenAI, or Anthropic APIs including prompt design and tool calling; working knowledge of embeddings, vector search, and RAG patterns.
- Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience; Mumbai location with office attendance required.
Ideal Candidate Profile
- Experience operating independently to deliver complex AI-driven modules from vague requirements to production.
- Strong backend engineering focus with emphasis on AI model orchestration, prompt engineering, and system reliability.
- Practical knowledge of AI tooling and optimization balancing AI response quality, latency, and cost; familiar with AWS fundamentals and production databases.