Job Description: Senior Full-Stack AI Engineer (AI Agent Platform)
Role Overview
We are looking for a Senior Full-Stack AI Engineer to join our team and lead development on Tekonika.
In this role, you will bridge the gap between frontend interfaces, high-performance backends, data warehouses, and cutting-edge AI agent orchestration. You will build
and scale autonomous agent systems capable of querying data, executing sandbox code, managing marketing cohorts, and triggering cold outreach campaigns.
Our architecture is a monorepo powered by Turborepo and Bun, running a LangGraph agent server and a Hono backend API, with a React 19 frontend and Kubernetes
deployments. If you love building complex AI-native systems, optimizing data pipelines, and implementing high-fidelity interfaces, this role is for you.
Key Responsibilities
AI Agent Engineering: Design, implement, and optimize stateful multi-agent workflows using LangGraph and LangChain for marketing analytics, lead scoring,
and automatic campaign generation.
Backend API Development: Write fast, lightweight, and type-safe API services in TypeScript using the Hono framework on the Bun runtime.
Data Integration & Warehousing: Query and manage marketing audiences and cohorts using Google BigQuery, and manage transactional application data in
PostgreSQL via Prisma ORM.
Real-time Frontend Development: Build reactive, accessible, and highly aesthetic user interfaces in React.js using TanStack Router, TanStack Query, and Radix
UI/Base UI primitives.
Asynchronous Processing: Build and scale background workers and job queues using Redis and BullMQ to handle high-throughput marketing data syncing
and web scraping.
Infrastructure & CI/CD: Manage containerized services using Docker and orchestrate them with Kubernetes (using Kustomize). Maintain automated CI/CD
pipelines via GitHub Actions.
Observability & Standards: Track LLM completions and cost performance with Langfuse, and maintain strict code quality standards using Ultracite (Oxlint +
Oxfmt) and ESLint.
Technical Stack Requirements
1. AI, LLM & Agent Orchestration (Core)
LangGraph & LangChain: Extensive experience building stateful, cyclic graphs, memory savers (e.g., custom PostgreSQL checkpoints), and tool-calling
schemas.
Langfuse: Experience with LLM tracing, evaluation, prompting registries, and analytics.
APIs: Integration experience with Anthropic (Claude Sonnet 4.6), Google Vertex AI (Gemini), and OpenAI APIs (e.g., Whisper, GPT-4o).
2. Backend & Database
Runtime: Bun (as runtime, test runner, and package manager).
Framework: Hono (routing, middlewares, auth context).
Database & ORMs: Prisma ORM, PostgreSQL (Supabase / local), and Google BigQuery.
Authentication: Better Auth (handling organizations, session hooks, and service-to-service internal keys).
Queues: Redis & BullMQ (background job execution).
3. Frontend Client
Core: React.js (React 19), Vite.
Routing & State: TanStack Router (file-based routing) and TanStack Query (server state synchronization).
UI & Styling: Radix UI / @base-ui/react primitives, Tailwind CSS (Tailwind v4 features), and Lucide Icons.
4. DevOps & Cloud
Docker & K8s: Building multi-stage Dockerfiles and deploying manifests with Kubernetes Kustomize.
Cloud: Google Cloud Platform (GCP) and AWS S3 / Google Cloud Storage.
CI/CD: GitHub Actions (writing workflows, caching build layers, auto-formatting, and deploying to clusters).
Key Qualifications
4+ years of professional experience in full-stack software development.
2+ years of experience working directly with LLMs, prompt engineering, and building agentic workflows (specifically LangGraph/LangChain).
Deep understanding of TypeScript, monorepos, and modern build/runtime systems (like Turborepo and Bun).
Experience handling database performance, writing raw SQL for BigQuery/PostgreSQL, and optimizing query speeds.
Excellent understanding of CI/CD concepts and managing services on Kubernetes clusters.
Pay: ₹379,799.93 - ₹1,632,029.94 per year
Benefits:
Work Location: Hybrid remote in Gurugram, Haryana (Gurugram)
