AI Fullstack Engineer

Innowhyte; Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Innowhyte is seeking a software engineer to design and ship full-stack AI features end-to-end in Bengaluru. You will build agent harnesses, manage retrieval and context systems for complex documents, and push prototypes through production with strong observability and cost discipline.

You will work with Next.js/TypeScript on the frontend, Python on the backend, and leverage LangChain/LlamaIndex in a cloud environment (AWS/GCP/Azure) while ensuring robust evaluation and compliance with system

Qualifications

• 2+ years of professional software engineering experience, with 1-2+ years shipping generative AI applications to production.
• Strong front-end (Next.js / TypeScript) and Python back-end skills, with a solid grasp of system design.
• Working knowledge of LLM fundamentals and a clear-eyed view of their limitations and failure modes.
• Has shipped at least one RAG system or agent to production, and built the agent harness around it (orchestration, tools, evals, observability).
• Hands-on experience with an agent framework (LangChain, LangGraph, LlamaIndex, or similar), or has built their own agent runtime/harness and can clearly justify why it beats reaching for a framework.
• Production experience with a major cloud (AWS / GCP / Azure), a relational database (Postgres preferred), and object storage.
• Fluent daily use of coding agents (Claude Code, Cursor, Copilot, or similar).

Responsibilities

• Design and ship full-stack AI features end-to-end, from the user-facing surface to the services and agent runtimes behind them.
• Build and operate agent harnesses (tool use, planning, memory, eval loops, guardrails) that reason over long, complex contracts and the varied document types around them.
• Own retrieval and context systems for high volumes of complex documents: chunking, embeddings, vector indexes, hybrid search, re-ranking, and citation-grounded generation.
• Take prototypes to production: observability, evaluation, regression suites, latency and cost budgets, prompt and model version management.
• Drive system-design decisions across services, data stores, model providers, and infrastructure.
• Use coding agents fluently as a daily driver to ship more, faster, without losing quality.

Skills

Front-end development

Python back-end

System design

LLM fundamentals

Agent frameworks

Cloud experience

Postgres

Tools

LangChain

LangGraph

LlamaIndex

Claude Code

Cursor

Copilot

AWS

GCP

Azure

PostgreSQL

Object Storage

Job description

Responsibilities:

• Design and ship full-stack AI features end-to-end, from the user-facing surface to the services and agent runtimes behind them.
• Build and operate agent harnesses (tool use, planning, memory, eval loops, guardrails) that reason over long, complex contracts and the varied document types around them.
• Own retrieval and context systems for high volumes of complex documents: chunking, embeddings, vector indexes, hybrid search, re-ranking, and citation-grounded generation.
• Take prototypes to production: observability, evaluation, regression suites, latency and cost budgets, prompt and model version management.
• Drive system-design decisions across services, data stores, model providers, and infrastructure.
• Use coding agents fluently as a daily driver to ship more, faster, without losing quality.

Requirements:

• 2+ years of professional software engineering experience, with 1-2+ years shipping generative AI applications to production.
• Strong front-end (Next.js / TypeScript) and Python back-end skills, with a solid grasp of system design.
• Working knowledge of LLM fundamentals and a clear-eyed view of their limitations and failure modes.
• Has shipped at least one RAG system or agent to production, and built the agent harness around it (orchestration, tools, evals, observability).
• Hands-on experience with an agent framework (LangChain, LangGraph, LlamaIndex, or similar), or has built their own agent runtime/harness and can clearly justify why it beats reaching for a framework.
• Production experience with a major cloud (AWS / GCP / Azure), a relational database (Postgres preferred), and object storage.
• Fluent daily use of coding agents (Claude Code, Cursor, Copilot, or similar).

Even Better If:

• Experience with model evaluation tooling (Braintrust, LangSmith, Arize, Phoenix, LangFuse).
• Background in a compliance-heavy or regulated domain, working with sensitive data (SOC 2, ISO 27001, HIPAA-style regimes) and the engineering practices that come with it.
• Open-source contributions of any kind.