SSE (GenAI Developer)

3 - 8 years

40 - 50 Lacs

Posted:1 day ago| Platform: Naukri logo

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Work Mode

Hybrid

Job Type

Full Time

Job Description

AI Product Engineer (GenAI Full-Stack)

Mission: Build AI-powered prototypes quickly and scale them into production-grade applications. This role owns the user-facing layer of our AI initiatives. These roles are key to accelerating AI adoption across the organization by rapidly prototyping solutions and scaling those that deliver impact. Phase 1: Rapid prototyping for internal validation. Phase 2: Scaling validated prototypes into secure, production-ready, customer-facing applications.

Responsibilities

  • Translate business requirements into AI-assisted Figma prototypes and working MVPs.
  • Build front-end apps (React, Next.js, Streamlit) and back-end APIs (FastAPI/Node).
  • Integrate RAG pipelines and agentic AI workflows into apps.
  • Connect with enterprise APIs (Jira, Salesforce, ServiceNow, HRIS, Datadog).
  • Use AI coding tools (Cursor, GitHub Copilot, Replit Agents) to accelerate development.
  • Implement telemetry, feature flags, authentication (OAuth/OIDC), and logging.
  • Collaborate with AI Platform Engineer to ensure accuracy, safety, and governance.
  • Work with Product Managers and Designers to refine UX for customer-facing applications.

Desired Skills (High Priority Low Priority)

  • Applied GenAI: Hands-on with RAG pipelines and Agentic AI frameworks (LangChain, Autogen, CrewAI, OpenAI function calling).
  • AI-Assisted Development: Proficient with Cursor, Copilot Agent Mode, Replit Ghostwriter/Agents.
  • Frontend Prototyping: React/Next.js, Streamlit, Tailwind/shadcn.
  • Backend APIs: Python (FastAPI/Flask), Node.js.
  • Integration Expertise: REST/GraphQL APIs, enterprise SaaS connectors.
  • Prompt Engineering: Designing structured, reliable prompts.
  • Figma + AI Plugins: Stitch, Uizard, Galileo AI for rapid prototyping.
  • Basic NLP Understanding: Summarization, classification, sentiment.
  • Data Handling: Basic ETL from CSVs, APIs.
  • DevOps Basics: Auth/RBAC, deployment (Vercel/Streamlit Cloud).
  • Production Standards: Error handling, accessibility, responsive design for customer-facing features.

Education

Bachelors or Master’s degree in Computer Science, Software Engineering, Human-Computer Interaction, or related field. 

Good-to-Have Qualifications

  • Experience in startup or innovation lab environments where rapid PoC delivery is common.
  • Familiarity with enterprise SaaS platforms (Salesforce, ServiceNow, Jira, Workday).
  • Experience deploying apps to cloud platforms (AWS Amplify, Vercel, Streamlit Cloud).
  • Participation in hackathons, open-source contributions, or AI prototype showcases.
  • Awareness of AI ethics and governance (bias, hallucinations, data privacy).

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