Full Stack Engineer

Full Stack Developer – GenAI Portfolio Company:

Insight Global (on behalf of our client) Location:

Remote - 10 am - 6 pm ist Compensation:

17–22 LPA (based on experience) Start Date:

Immediate (No notice period preferred) A vailability:

Must be able to start within 2–3 weeks or sooner Notice Period:

ASAP hire —

only apply if you can start within 2 weeks of offer Interview Process:

Priority scheduling for candidates who message on LinkedIn with their resume

IMMEDIATE JOINERS ONLY

Role Overview Insight Global is seeking a highly skilled

Full Stack Developer

to support a global consulting firm’s rapidly expanding

GenAI portfolio . You will help design, build, and deploy custom AI‑powered platforms, including automation products like

Proposal Excellence

and other next‑generation GenAI tools. You’ll be working in a fast‑paced, experimental environment where agility, creativity, and strong engineering discipline are essential. This position is fully remote in India.

Required Skills & Experience 5+ years

of full stack development experience (frontend + backend). Proficiency in

Python ,

JavaScript/TypeScript ,

React , and

Node.js . Hands‑on experience with

GenAI/LLM technologies

(OpenAI APIs, LangChain, embeddings, etc.). Experience building modern

web applications

and supporting internal tool adoption. Working knowledge of

Kubernetes

and containerized deployments. Strong understanding of

API design , data integration, distributed systems, and

microservices architecture . Comfortable working in

agile environments

with distributed global teams. Ability to thrive in a fast‑paced, experimental, highly collaborative environment.

Key Responsibilities

Full Stack Development Build and maintain full stack applications across both frontend and backend components. Develop scalable APIs, microservices, and data‑integrated features powering GenAI workflows. Support global teams with tool adoption, platform enhancements, and new feature rollout. GenAI / LLM Engineering Work hands‑on with GenAI technologies such as OpenAI APIs, LangChain, embeddings, and LLM‑powered automation flows. Implement retrieval‑augmented generation (RAG) pipelines and integrate LLMs into end‑to‑end solutions. Cloud & DevOps Develop and maintain solutions using cloud platforms such as Azure, AWS, or GCP. Deploy and manage applications in

Kubernetes

environments. Contribute to CI/CD pipelines supporting reliable and iterative product releases. Team Collaboration Work closely with engineering, product, and global stakeholders in agile environments. Participate in rapid experimentation cycles with minimal supervision.