Salary
≈ $20k – $52k per year (Estimated)
Location
In office (Hyderabad)
Seniority
Senior · 5+ years exp
Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on May 18, 2026. Vedya Labs scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Vedya Labs accelerates AI adoption through cutting-edge solutions in Edge AI, Embedded Software, IoT, Industry 4.0, and GenAI. With over 12 years of expertise, we collaborate with top tech companies to drive digital transformation and innovation.
Experience 5 years
Location Hyderabad (On-site)
Type Full-time
The Role
We're looking for a Full-Stack AI Engineer who's equally comfortable shipping a clean React UI, a FastAPI backend, and an LLM-powered agent that works in production. Here, AI isn't bolted on - it's the product. You'll own features end-to-end alongside a small, high-trust team that ships fast and cares about quality.
What You'll Do
- Build full-stack features across frontend, backend, data, and AI layers.
- Design and ship agentic AI systems with LangChain and modern orchestration patterns.
- Make real architecture and system design calls - APIs, scale, cost, trade-offs.
- Review code, mentor where it helps, and contribute to engineering culture and standards.
What We're Looking For
Around 5 years of strong full-stack experience, with real depth in modern AI engineering. Specifically:
- Frontend - Frontend: solid command of JavaScript/TypeScript and React. You can build clean, responsive UIs and you care about UX details.
- Backend - Backend: production experience with Python and FastAPI. You write APIs that are clean, tested, and easy to evolve.
- Data - Databases: comfortable across SQL (PostgreSQL/MySQL) or NoSQL (MongoDB, Redis, or similar). You think about data models, not just queries.
- GenAI - GenAI: hands-on with LangChain, prompt engineering, RAG, and agentic AI patterns. You've shipped LLM features that real users depend on.
- AI Tooling - AI Tooling: fluent with Claude Code, Cursor, Copilot, and similar tools. You know when to lean on them and when not to.
- Architecture - strong grasp of system design, distributed systems basics, and the trade-offs that come with scale.
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