Job Description:

About the Role

Evernine Brands (EBPL) is building an AI-native marketing intelligence platform. We are a small, fast-moving engineering team. You will build web app features in React + TypeScript, develop and extend our Python backend and APIs, contribute to our Python-based AI agents and automations, and build integrations across our platform and tools. This is a high-ownership role with broad surface area and fast shipping — and you will provide real engineering depth so that we are never single-threaded on any system.

• Core Focus: Autonomous Agents, Multi-Agent Systems, and LLM Engineering

Role Overview

We are seeking a highly skilled and self-directed Full Stack Engineer with a deep specialization in Agentic AI to join our engineering team in our Delhi office. In this role, you will bridge the gap between robust, production-grade full-stack software engineering and cutting-edge cognitive systems. You will be responsible for designing and deploying end-to-end user interfaces, building resilient Python-based back-end APIs, and orchestrating complex, autonomous multi-agent workflows that connect our internal tools and third-party systems.

What You'll Do

• Front-End Execution: Build new pages, flows, and features in React + TypeScript, and ship them into our core web application.

• Back-End Engineering: Develop and maintain backend services and APIs in Python (utilizing our existing API framework).

• Database Design: Design and query PostgreSQL schemas for the features you build.

• AI Feature Engineering: Build LLM-powered features and automations in Python — utilizing tool/function calling, RAG (Retrieval-Augmented Generation), and automated pipelines.

• Agentic Orchestration: Build agent-based workflows, autonomous agents, and internal automations that connect our tools and services, with appropriate review and approval steps.

• Third-Party Integrations: Build integrations between our platform and third-party services (CRMs, ad platforms, email/SMS, analytics, payments) via REST APIs and webhooks.

• Systems Quality: Own quality for what you ship: testing, error handling, monitoring, and code review.

• Systems Redundancy: Provide engineering coverage across frontend, backend, and AI so the team has genuine redundancy.

Must-Have Qualifications

• Agentic / AI Platform Experience (MOST IMPORTANT): Hands-on experience building production-level AI agents, autonomous agents, or multi-agent systems.

  • Active implementation experience using framework technologies such as LangChain, LangGraph, CrewAI, or AutoGPT.

  • OR scaling agent workflows within Cognitive Studios (Google Agent Studio / Vertex / Gemini, Microsoft Copilot Studio, or OpenAI Assistants API).

• Full-Stack Experience: 2+ years building and maintaining production web applications across the full stack.

• Front-End Proficiency: Strong React with TypeScript — including hooks, typed components, state management, component architecture, and consuming REST APIs.

• Back-End Proficiency: Strong Python backend development utilizing modern API frameworks (FastAPI / Django / Flask).

• Database Modeling: Solid PostgreSQL / SQL skills and sound relational data modeling.

• LLM Integration: Direct experience building LLM-powered applications in Python using OpenAI API, Anthropic / Claude API, and Gemini API. Fluent in advanced prompt engineering, "RAG" tool/function calling, and structured JSON outputs.

• REST Protocols: Strong REST API design skills — managing endpoints, handling rate limits, webhooks, pagination, and multi-tenant authorization.

• DevOps Workflow: Comfortable with Git, CI/CD, and cloud deployment (GCP environment preferred).

• Understanding of the Model Context Protocol (MCP) — building, consuming, or hosting MCP servers and LLM tooling connectors.

• Startup Mindset: Self-directed starter who is able to scope, break down, and ship features rapidly.

Nice-to-Have (Bonus Skills)

• Exposure to Flutter / mobile development (to support our mobile work when needed).

• Experience with Vector databases (pgvector, Pinecone, Weaviate) for semantic retrieval.

• Familiarity with Google Workspace APIs or Apps Script (Drive, Sheets, Gmail, Chat).

• Agent evaluation & reliability pipelines — prompt evaluations, guardrails, and failure handling.

• Workflow-automation platforms (n8n, Temporal, Zapier/Make) or modern event-driven system logic.

• Martech / adtech domain experience.

• Observability experience (logging, metrics, tracing).

What We Offer

• Foundational impact at an AI-native company, with real ownership.
• A small, senior, fast-moving team and a flat, fast decision-making culture.