Full Stack AI Engineer
Vinmar International
- Location
- Onsite (Mumbai, Maharashtra)
- Employment
- Full-time
- Level
- Mid Level
Posted 1 week ago
About the role
Vinmar International is seeking a Full Stack AI Engineer to design and build AI-native features, including agentic systems and RAG pipelines, within a global plastics and chemicals distribution company.
Skills
ASP.NET Core
Python
FastAPI
React
Next.js
TypeScript
RAG
LangChain
LangGraph
Vector Databases
SQL
Prompt Engineering
Agentic Systems
CI/CD
LLM Evaluation
Full-stack Development
Full job details
- Design and build full-stack AI features, including tables, document-centric interfaces, review flows, and real-time or streaming interactions.
- Develop agentic systems with tool calling, multi-step workflows, RAG, and structured output handling.
- Build backend services using ASP.NET Core Web API and Python (FastAPI), and integrate them with React/Next.js frontends.
- Implement and improve RAG pipelines, covering chunking, embedding selection, vector store integration, and retrieval quality evaluation.
- Design AI-native UX patterns: confidence indicators, citations and source grounding, fallback states, edit/retry flows, and human review steps.
- Write evaluation tests before shipping new AI capabilities, using golden datasets, regression gates, and CI controls.
- Contribute to evaluation pipelines that combine deterministic metrics with LLM-as-judge approaches.
- Build systems that degrade gracefully when model outputs are unexpected.
- Manage context windows through token budgeting, truncation, and tool-call state persistence.
- Prototype quickly with AI tooling, then validate production artifacts against defined quality gates before promotion.
Education and experience
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience.
- 3+ years building production software, including full-stack applications and/or AI-enabled systems.
- Experience contributing to user-facing AI product features, from backend through frontend.
- Experience with agentic systems in production or pre-production (tool calling, multi-step workflows, RAG, structured outputs).
- Exposure to evaluation frameworks such as golden datasets, regression gates, or CI quality controls.
Full-stack product engineering
- Hands-on experience with .NET Core, ASP.NET Core Web API, SQL, and Microsoft technologies.
- Frontend skills in React and/or Next.js, TypeScript, component-based UI, API integration, and state management.
- Experience building tables, document-centric interfaces, review flows, or streaming experiences.
- Understanding of UX patterns for AI systems (confidence, citations, fallbacks, edit/retry, human review).
AI platform engineering
- Python proficiency, including FastAPI, Pydantic v2, async patterns, and pytest.
- Hands-on experience with LangChain and/or LangGraph: stateful graphs, tool integration, checkpointing, and streaming.
- Prompt engineering skills: structured output design, system prompt construction, and multi-turn context management.
- Experience with RAG pipelines and familiarity with vector databases such as pgvector and/or OpenSearch.
- Familiarity with LLM evaluation: golden dataset design, metric definition, and regression gates.
- Awareness of context window management strategies.
Generative AI and agentic systems
- Regular use of AI coding assistants (Cursor, GitHub Copilot), with good judgement about where generated code is reliable and where it needs scrutiny.
- Familiarity with multi-agent concepts: orchestration logic, tool interfaces, and failure-handling patterns.