Full Stack AI Engineer

Location: Noida (On-site)

Company: Zynence Labs Pvt. Ltd.

Experience: 0–2 years

Employment Type: Full-time

About Zynence

Zynence is building an AI-native, full-lifecycle hardware engineering platform, a connected workspace that takes a hardware product from requirements and system architecture through BOM/cost, firmware, schematic/PCB, simulation, validation, and manufacturing. The platform runs on eleven purpose-built AI agents and a RAG-grounded knowledge layer, with a core architectural bet that generative AI handles drafting and structuring while deterministic engines compute anything an engineer would sign off on as a number, cost rollups, component derating, trace current capacity, battery runtime. We're targeting the sectors where design traceability is non-negotiable: medtech, aerospace & defense, robotics, EV hardware, and industrial IoT.

Role Overview

We're looking for an AI/ML Engineer who is equally comfortable building and shipping full-stack web features and building the AI/ML systems that power them. You'll work across our agent architecture and knowledge layer, from retrieval pipelines and LLM-powered agents to the web application and cloud infrastructure that put them in front of users. This is a hands-on, build-things role at an early-stage product company: you'll ship real features that go into a live platform, not a research sandbox.

Key Responsibilities

AI/ML & Agent Development

• Design, build, and iterate on LLM-powered agents within our multi-agent architecture (AGT-001–AGT-011).
• Build and improve retrieval-augmented generation (RAG) pipelines for our knowledge layer (AskZynence), including embedding generation, vector search, and retrieval quality tuning.
• Work within our generative/deterministic split — know when a task belongs to a language model and when it belongs to a deterministic engine, and build accordingly.
• Evaluate and integrate LLM APIs (OpenAI, Anthropic, or similar), including prompt design, structured output handling, and cost/latency tradeoffs.
• Contribute to data pipelines and evaluation frameworks that measure agent output quality over time.

Full-Stack Web Development

• Build and ship features across the frontend (React) and backend (Node.js/Express or equivalent) of the Zynence platform.
• Design and consume REST APIs; work comfortably with relational databases (PostgreSQL) and, where relevant, vector-enabled extensions (pgvector).
• Write clean, maintainable, well-tested code that other engineers can build on.
• Collaborate with the founders and engineering team to translate product requirements into working, production-ready features.

Deployment & Cloud Infrastructure

• Deploy and maintain services on a cloud platform (AWS preferred; GCP/Azure experience also valued) — compute, storage, managed databases, and networking basics.
• Set up and maintain CI/CD pipelines for reliable, repeatable deployments.
• Use containerization (Docker) and basic orchestration where appropriate.
• Monitor application health and troubleshoot production issues across the stack, from infrastructure to application code to model behavior.

Qualifications

Required

• B.Tech/B.E. in Computer Science, IT, or a related field (or equivalent practical experience).
• 0–2 years of hands-on experience building software - internships, personal projects, or professional work all count.
• Working proficiency in a MERN-equivalent stack: React on the frontend; Node.js/Express (or a comparable backend framework) and a relational or document database on the backend.
• Practical exposure to AI/ML concepts, this can be coursework, personal projects, hackathons, or professional experience: working with LLM APIs, embeddings, vector search, or classical ML.
• Comfort with Python, since most of our ML/agent tooling is Python-based even where the web app is JavaScript/TypeScript.
• Some exposure to deploying an application to the cloud (AWS, GCP, or Azure) — you don't need to be a DevOps expert, but you should have shipped something beyond localhost.
• Strong fundamentals in data structures, algorithms, and API design.

Preferred

• Hands-on experience with RAG pipelines, vector databases (pgvector, Pinecone, Weaviate, or similar), or LLM agent frameworks (LangChain, LlamaIndex, or custom agent architectures).
• Experience with prompt engineering and structured LLM output (function calling, JSON mode, or similar).
• Exposure to Docker and CI/CD tooling (GitHub Actions or similar).
• Interest in or exposure to hardware/engineering domains (electronics, embedded systems, PCB design, or manufacturing) — not required, but a genuine plus given what we're building.
• Experience working in a small team or startup environment where you own a feature end-to-end.

What We Look For

• Engineers who can move between build the ML pipeline and ship the UI for it in the same week.
• Strong ownership — you follow a feature from idea to production, not just to a pull request.
• Curiosity about both AI/ML and full-stack engineering — genuine interest in both sides of this role, not just one.
• Comfort with ambiguity: this is an early-stage product, and priorities will shift as we learn from real users.
• Clear communication — you can explain a technical tradeoff to a non-technical founder and a design decision to another engineer.

Why Join Zynence

• Build core AI/agent infrastructure for a category-defining product from an early stage, your work will directly shape the platform's architecture, not just extend it.
• Work across the full stack: AI/ML, backend, frontend, and cloud infrastructure, rather than being siloed into one layer.
• Direct collaboration with the founders on product and technical decisions.
• Real ownership on a live, filed-IP platform, not a side project or a research exercise.
• Fast learning curve across modern AI engineering (agents, RAG, LLM integration) and production web/cloud engineering.

How to Apply

Apply through LinkedIn and send your resume, along with links to any relevant projects (GitHub, deployed apps, or write-ups), to [HIDDEN TEXT] Subject: Application for Full Stack AI Engineer – Zynence