Technical Lead - Agentic AI Platform

NST Cyber - Your Trusted Enterprise CTEM Partner; India; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

NST Cyber - Your Trusted Enterprise CTEM Partner is seeking a hands-on Technical Lead to own the architecture, development, and delivery of a cloud-native Agentic AI platform. You will guide a team of 10–12 engineers and drive architecture reviews, critical implementation, and engineering governance.

You should have deep experience in Python, FastAPI, NestJS, AWS (EKS, Fargate, ECS), Kubernetes, Kafka, and modern data platforms.

Qualifications

• Strong hands-on experience with Python, FastAPI, and NestJS.
• Experience with TypeScript and Angular.
• Strong AWS experience including EKS, Fargate, ECS, IAM, VPC, S3, and CloudWatch.
• Strong understanding of Kubernetes, Docker, autoscaling, and containerized workloads.
• Experience with Agentic AI platforms and LangGraph.

Responsibilities

• Shape the long-term architectural vision and technical roadmap of the Agentic AI platform.
• Lead, mentor, and foster technical excellence across a team of 10-12 engineers.
• Establish governance for API design, observability, and production security.
• Direct AI agent workflows using LangGraph and ReAct patterns, memory systems, and RAG.
• Collaborate with Product, Security, and Engineering stakeholders on reliability and cost telemetry.

Skills

Python

FastAPI

NestJS

TypeScript

Angular

Tools

MongoDB

Graph databases

Qdrant

Apache Kafka

Docker

Kubernetes

CI/CD

Infrastructure as Code

Job description

Role Overview

We are seeking a hands-on Technical Lead to lead the architecture, development, and delivery of a cloud-native Agentic AI platform. The role requires strong technical depth across backend engineering, frontend technologies, AWS, Kubernetes, distributed systems, AI agents, data platforms, and DevOps. The candidate will lead a team of 10-12 engineers while remaining actively involved in architecture, design reviews, critical implementation, troubleshooting, and engineering governance.

Core Technical Ownership & Engineering Competencies

• Individual Ownership & Architectural Leadership:Take personal ownership of core system design, architecture, and module deliverables, demonstrating independent technical leadership rather than relying purely on generalized team contributions.


• Quantified System Design & Scale:Architect high-throughput distributed systems, establishing clear performance baselines, request volume handling, and quantifiable latency optimizations.


• Advanced Backend & Framework Depth:Engineer robust backend services utilizing advanced framework patterns, including custom dependency injection setups, middleware, custom guards, and interceptors in FastAPI and NestJS.


• Cloud Infrastructure & Orchestration:Directly configure and manage production cloud infrastructure on AWS, leveraging Amazon EKS, Fargate, ECS, and Karpenter for dynamic container provisioning and reliability.


• Database Internals & Performance Tuning:Optimize data persistence layers by tuning database internals, including complex indexing strategies, query execution plans, schema design, and transaction handling.


• Event-Driven & Message Queue Architecture:Design and operate resilient event-driven pipelines using Apache Kafka, managing producer-consumer topologies, event streams, and dead-letter queue (DLQ) retry workflows.


• Software Quality & Engineering Governance:Uphold rigorous engineering standards through automated test coverage, test-driven development (TDD), CI/CD quality gates, and code review excellence.

Strategic Leadership & Key Responsibilities

• Strategic Architecture & Roadmap:Shape the long-term architectural vision and technical roadmap of the Agentic AI platform, making sound decisions across scalability, security, performance, cost, and delivery.


• Engineering Leadership & Mentorship:Lead, mentor, and foster technical excellence across a high-performing team of 10-12 engineers, building strong accountability and structured execution.


• Governance & Security Standards:Establish enterprise-grade governance frameworks for API design, system observability, auditability, and production security.


• Agentic AI & Workflow Orchestration:Direct the implementation of advanced AI agent workflows utilizing LangGraph and ReAct patterns, memory systems, tool execution, RAG, and execution guardrails.


• Cross-Functional Collaboration:Partner closely with Product, Security, and Engineering stakeholders to align platform reliability, cost telemetry, and readiness objectives.

Required Technical Skills

• Strong hands-on experience with Python, FastAPI, and NestJS.


• Experience with TypeScript and Angular.


• Strong AWS experience, including Amazon EKS, Karpenter, Amazon ECS, AWS Fargate, IAM, VPC, S3, and CloudWatch.


• Strong understanding of Kubernetes, Docker, autoscaling, and containerized workloads.


• Experience with Agentic AI platforms and hands-on LangGraph experience.


• Good understanding of Reason and Act (ReAct) patterns, LLM integration, tool calling, agent memory, RAG, and HITL workflows.


• Experience with execution guardrails (NeMo Guardrails) and OpenLLMetry / OpenTelemetry.


• Strong experience with MongoDB, graph databases, vector databases (Qdrant), and Apache Kafka.


• Good understanding of CI/CD, infrastructure as code, monitoring, security, and production operations.

Desired Certifications

• AWS Certified Solutions Architect or Developer


• AI, Machine Learning, Generative AI, or LLM-related Certification


• Kubernetes Certification (e.g., CKA or CKAD)