Urgent Hiring_Full Stack with Agentic AI

Genpact Ltd.

Dadri, Bengaluru

Hybrid

INR 2,400,000 - 4,000,000

Full time

5 days ago
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Job summary

Genpact Ltd. invites applications for a Manager, Full Stack Application Development (Agentic AI). The role blends hands-on full stack engineering with agentic AI expertise to build customer-facing platforms, AI copilots, and RAG workflows at enterprise scale.

The candidate will own the full SDLC, deliver secure and scalable apps, and drive cloud-native modernization using APIs and microservices. Strong experience in Python/JavaScript stacks, React/Angular, and AI frameworks is required.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
  • Relevant years of professional software engineering experience.
  • Strong experience building enterprise-scale full stack applications.
  • Proven experience delivering secure, scalable, customer-facing applications.
  • Experience working independently while driving large and complex initiatives.
  • Strong stakeholder management, communication, and problem-solving capabilities.

Responsibilities

  • Design, develop, and support client-facing web applications, digital platforms, APIs, and enterprise solutions.
  • Build modern, responsive, and intuitive user interfaces using React, Angular, TypeScript, JavaScript, HTML5, and CSS.
  • Develop scalable backend services using Python (FastAPI), Java Spring Boot, Node.js, or equivalent technologies.
  • Design and implement secure REST APIs, microservices, and event-driven architectures.
  • Translate business requirements into scalable technical solutions through direct engagement with business stakeholders.
  • Own the complete software development lifecycle from concept to production support.
  • Deliver highly available, resilient, secure, and performant applications.
  • Drive modernization initiatives using cloud-native, API-first, microservices-based architectures.

Skills

Full stack development
Client-facing
Independent contributor
Stakeholder management

Education

Bachelor's or Master's degree in CS/Engineering/IT

Tools

React
Angular
TypeScript
Python
FastAPI
Spring Boot
Node.js
LangChain/LangGraph/Semantic Kernel
Azure/OpenAI/AKS

Job description

Inviting applications for the role of Manager, Full Stack Application Development (Agentic AI)

We are seeking a highly skilled hands-on engineer who combines strong Full Stack Development capabilities with modern Agentic AI expertise, capable of building customer-facing digital platforms, AI copilots, RAG applications, and autonomous agent workflows while maintaining enterprise-grade standards for scalability, security, resiliency, observability, and user experience. This role requires strong full-stack engineering capabilities across frontend, backend, APIs, cloud-native architectures, and DevOps, combined with hands-on experience in Generative AI, AI Agents, Retrieval-Augmented Generation (RAG), and LLM orchestration.

Responsibilities:
Full Stack Application Development
  • Design, develop, and support client-facing web applications, digital platforms, APIs, and enterprise solutions.
  • Build modern, responsive, and intuitive user interfaces using React, Angular, TypeScript, JavaScript, HTML5, and CSS.
  • Develop scalable backend services using Python (FastAPI), Java Spring Boot, Node.js, or equivalent technologies.
  • Design and implement secure REST APIs, microservices, and event-driven architectures.
  • Translate business requirements into scalable technical solutions through direct engagement with business stakeholders.
  • Own the complete software development lifecycle from concept, design, development, testing, deployment, and production support.
  • Deliver highly available, resilient, secure, and performant applications.
  • Drive modernization initiatives using cloud-native, API-first, and microservices-based architectures.
Agentic AI Development
  • Design and build AI agents capable of reasoning, planning, tool utilization, and executing multi-step tasks autonomously.
  • Develop intelligent workflows using LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or similar frameworks.
  • Design and implement multi-agent systems comprising planners, executors, evaluators, orchestrators, and domain-specific agents.
  • Build agent memory systems, checkpointing, state management, guardrails, escalation mechanisms, and human-in-the-loop workflows.
  • Develop AI-enabled capabilities that improve operational efficiency, client experience, and business workflows.
  • Implement workflow orchestration, tool-calling, and autonomous decision-making capabilities using Large Language Models.
  • Evaluate and optimize agent performance, reasoning quality, task completion, and reliability.
  • Develop calibration frameworks and guardrails to improve agent accuracy and reduce hallucinations.
MCP & AI Platform Engineering
  • Design, develop, and maintain Model Context Protocol (MCP) servers and enterprise AI integration frameworks.
  • Build reusable MCP tools, resources, prompts, and connectors.
  • Develop scalable processes for onboarding and registering enterprise tools within MCP ecosystems.
  • Enable AI agents to securely interact with enterprise systems, APIs, business applications, and databases.
  • Develop reusable AI platform components supporting orchestration, memory, governance, and tool execution.
RAG & Knowledge Systems
  • Design and implement enterprise-grade Retrieval-Augmented Generation (RAG) solutions.
  • Develop document ingestion, chunking, indexing, retrieval, and ranking pipelines.
  • Implement semantic search, hybrid retrieval, metadata filtering, and contextual reasoning capabilities.
  • Work with embeddings and vector databases including Azure AI Search, Pinecone, FAISS, ChromaDB, and Weaviate.
  • Optimize AI applications for groundedness, accuracy, relevance, latency, scalability, and cost efficiency.
  • Evaluate retrieval and generation quality using standardized AI evaluation frameworks.
Cloud, DevOps & Platform Engineering
  • Deploy and manage cloud-native applications on Azure.
  • Build and maintain CI/CD pipelines, automated testing frameworks, and deployment automation processes.
  • Develop and manage containerized workloads using Docker and Kubernetes.
  • Implement Infrastructure-as-Code and DevSecOps best practices.
  • Ensure operational excellence, security, reliability, and scalability across distributed systems.
  • Collaborate with platform and cloud engineering teams to deliver enterprise-scale AI and digital solutions.
Observability & Monitoring
  • Configure OpenTelemetry instrumentation, distributed tracing, metrics, and logging.
  • Monitor application performance, AI agent executions, model calls, API requests, workflow latency, and infrastructure utilization.
  • Integrate telemetry with Grafana, Azure Monitor, Application Insights, Galileo, or equivalent observability platforms.
  • Build dashboards and alerts to proactively identify failures, bottlenecks, anomalies, and production issues.
  • Lead troubleshooting and production debugging of distributed applications and AI systems.
Enterprise Data Integration
  • Design and build integrations with MongoDB, PostgreSQL, SQL Server, Snowflake, and enterprise data platforms.
  • Develop APIs and services supporting transactional and analytical workloads.
  • Integrate AI applications with enterprise systems, workflow engines, document repositories, and business platforms.
  • Ensure secure handling of credentials, secrets, API keys, service identities, and authentication tokens.
Qualifications we seek in you!
Minimum Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
  • Relevant years of professional software engineering experience.
  • Strong experience building enterprise-scale full stack applications.
  • Proven experience delivering secure, scalable, customer-facing applications.
  • Experience working independently while driving large and complex initiatives.
  • Strong stakeholder management, communication, and problem-solving capabilities.
Technical Skills
Full Stack Development
  • Strong programming expertise in Python.
  • Experience with FastAPI, Spring Boot, Node.js, or similar backend frameworks.
  • Proficiency in React, Angular, TypeScript, JavaScript, HTML5, and CSS3.
  • Experience building REST APIs, microservices, and enterprise web applications.
  • Strong understanding of software design patterns, scalable architectures, and secure coding practices.
Agentic AI & GenAI
  • Hands-on experience with LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar agent frameworks.
  • Experience building AI agents, multi-agent systems, AI copilots, and workflow automation solutions.
  • Strong understanding of RAG, prompt engineering, tool calling, agent memory, orchestration, and AI evaluation frameworks.
  • Experience with embeddings, vector databases, and semantic search technologies.
Cloud & DevOps
  • Experience with Azure OpenAI, Azure AI Search, Azure Functions, App Services, and AKS.
  • Knowledge of Docker, Kubernetes, CI/CD pipelines, and cloud-native application development.
  • Familiarity with monitoring, observability, and OpenTelemetry.
Data & Integration
  • Experience with MongoDB, SQL Server, PostgreSQL, Snowflake, or similar databases.
  • Strong understanding of API integration, enterprise application integration, authentication, and authorization frameworks (OAuth/OIDC).
Architecture & Engineering
  • Strong understanding of microservices, distributed systems, scalability, resiliency, and performance optimization.
  • Experience designing modular, reusable, and enterprise-grade applications.
  • Excellent problem-solving, stakeholder management, and communication skills.
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