Software Engineer — AI & Full Stack

Requirements

• 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 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.

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 Azure and cloud edge platforms.
• Mentorship & Team Quality
• Review intern code — catching bugs and anti-patterns and turning every review into a learning opportunity.
• 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.