Software Engineer AI & Full Stack

Required Qualifications

- 3–5 years of experience shipping software in small, fast-moving teams — end-to-end ownership, not just feature contributions.
- Hands-on experience building with LLMs in production — token mechanics, context windows, prompt design, API management, and cost control.
- Proficiency with LangGraph for multi-agent orchestration. LangChain or equivalent is a plus.
- Full stack capability: React or Next.js frontend; Node.js and/or Python backend.
- Strong GitHub fluency — branching, code review, CI/CD, and clean commit discipline.
- Working knowledge of Microsoft Azure — deployments, storage, compute, and Azure OpenAI.
- Comfortable integrating third-party APIs and managing cloud infrastructure (object storage, queuing, database-as-a-service, edge deployment).
- Bachelor's in Computer Science or Engineering, or equivalent demonstrable experience.
- A hands-on experience on fine tuning the LLM models.

Preferred Skills

- Familiarity with RAG, vector databases, or semantic search.
- Understanding of agentic AI design patterns and multi-agent architectures.
- Exposure to GDPR or sensitive data handling in production.
- Prior experience mentoring junior developers or conducting structured code reviews.

Success Metrics

- Features shipped on time with production-quality code and no critical regressions.
- Measurable improvement in intern code quality over time — fewer bugs, cleaner commits, better structure.
- LLM integrations perform reliably — stable costs, correct token usage, consistent API behaviour.
- Git workflows followed consistently across the team.




- Zero critical data handling incidents.

You Will Thrive Here If You

- Have owned features from blank file to production — not just contributed to someone else's codebase.
- Have used LLMs in production and understand where they break.
- See mentoring interns as part of the job, not a distraction from it.
- Prefer high-trust small teams where your decisions are visible.

This Role Is Not For You If

- You need established processes and clearly scoped tickets to do your best work.
- You want to step back from hands-on building.
- You are more comfortable reviewing architecture decisions than making them.

Responsibilities

AI & Product Development

- Build and maintain LLM pipelines and multi-agent workflows using LangGraph, from architecture through to production.
- Integrate LLM provider APIs — managing prompt versioning, token budgets, rate limits, and inference costs.
- Own full stack features end-to-end: UI, API, infrastructure, and data layer.
- Work on 0-to-1 product development — features go from concept to production with minimal hand-holding.
- Manage deployments and infrastructure on Microsoft Azure and cloud edge platforms.

Mentorship & Team Quality

- Review intern code — catching bugs and anti-patterns and turning every review into a learning prospect.
- Guide junior developers through debugging and architectural decisions without creating dependency.
- Set and enforce Git workflows and coding standards across the team.
- Contribute to architecture discussions, surface risks early, and flag compliance concerns around audio, video, and personal data.

Top of Form

Bottom of Form

📌 AI Software Developer (Hyderabad Onsite) (Immediate Joiners)
🏢 Navsan
📍 Telangana