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Track Manager (Support & Operations)

India

Job Description

Track Manager (Support & Operations)

Gautam Buddha Nagar, Uttar Pradesh

Job Summary

Forward Deployment Engineer - AWS Agentic AI

Job Type

Full-Time

Experience

4-7 years overall; at least 2 years in Generative AI / Agentic AI with production delivery on AWS

Locations

Noida, Hyderabad, Chennai, Bangalore, Pune

Primary Focus

Customer-specific engineering, integrations, deployment, productionization and troubleshooting

Role Overview

We are looking for a Forward Deployment Engineer (FDE) to design, customize, integrate, deploy, troubleshoot, and operationalize enterprise Generative AI and Agentic AI solutions for customers on AWS. The FDE is a hands-on customer-facing engineer who turns reusable platform capabilities into working customer solutions and owns the implementation from technical discovery through production go-live and hypercare.

- Hands-on customer implementation engineer
- Heavy software and integration ownership
- Executes the customer deployment plan
- Escalates architecture/platform decisions when required

Typical time allocation
- ~70% engineering and integration
- ~20% customer interaction
- ~10% architecture contribution

Key Responsibilities

- Work directly with customer technical teams to understand application, infrastructure, data, integration, security, and operational requirements and translate them into implementable solutions.
- Participate in technical discovery sessions, solution workshops, demonstrations, proof-of-concepts, pilots, deployment planning, and go-live activities.
- Implement customer-specific Agentic AI solutions using Amazon Bedrock, Amazon Bedrock AgentCore, Python, and appropriate agent frameworks such as LangGraph, LangChain, Strands Agents, or other approved frameworks.
- Configure and customize reusable agents, Skills, tools, workflows, RAG components, prompts, and enterprise connectors for customer environments.
- Develop customer-specific integrations using REST APIs, AWS SDKs, MCP tools, databases, ITSM platforms, monitoring systems, identity services, and proprietary applications when reusable connectors are unavailable.
- Configure customer endpoints, authentication, authorization, IAM roles/policies, OAuth/API credentials, Secrets Manager, API Gateway, and other security controls required for integration.
- Deploy and operate customer solutions on AWS using services such as Amazon Bedrock AgentCore Runtime, Gateway, Memory and Identity, Lambda, ECS, EKS, API Gateway, EventBridge, Step Functions, SQS/SNS, S3, and related services.
- Configure customer-specific RAG and knowledge integrations, including data ingestion, retrieval, access control, and validation using customer-approved search, vector, database, and storage services.
- Implement logging, tracing, metrics, monitoring, evaluation, and operational dashboards using Amazon Bedrock AgentCore Observability, Amazon CloudWatch, AWS X-Ray/OpenTelemetry, and related capabilities.
- Execute functional, integration, security, performance, resiliency, evaluation, and user acceptance testing before production rollout.
- Troubleshoot production issues across agents, models, prompts, tools, APIs, RAG, authentication, networking, and AWS infrastructure; drive issues to closure.
- Analyze logs, traces, metrics, evaluation results, latency, token usage,



and failure patterns and implement corrective actions.
- Support CI/CD, environment promotion, versioning, releases, rollback, and production deployment activities.
- Optimize solutions for reliability, scalability, latency, usability, and AI inference cost.
- Document customer architecture, integrations, configuration, deployment steps, operational runbooks, troubleshooting procedures, and support information.
- Conduct knowledge transfer to customer teams and internal support/BAU teams and support production hypercare.
- Identify recurring customer requirements and provide structured feedback to Agent Development / Platform Engineering teams for reusable platform improvements.

Skill Requirements

Must Have Skills

- Solid Python programming and software engineering fundamentals.
- Hands-on experience with LLMs, RAG, prompt engineering, agentic workflows, tool/function calling, structured outputs, and multi-agent systems.
- Hands-on experience with Amazon Bedrock and/or Amazon Bedrock AgentCore for production agent solutions.
- Strong REST API development and integration experience; comfortable working with JSON, YAML, AWS SDKs, and enterprise APIs.
- Working knowledge of AWS IAM, role-based access, OAuth, API keys, Secrets Manager, authentication, authorization, and secure service-to-service integration.
- Hands-on experience with AWS and at least one production deployment model using ECS, EKS, Lambda, or AgentCore Runtime.
- Experience with Git, CI/CD, Docker, and production deployment practices.
- Experience with logging, monitoring, tracing, debugging, and production incident troubleshooting.
- Good understanding of databases, SQL, enterprise data sources, and RAG implementation patterns.
- Good understanding of Responsible AI, security, data protection, and enterprise deployment requirements.
- Strong communication skills and ability to work directly with customer technical stakeholders.

Preferred Skills

- Experience with Amazon Bedrock, AgentCore Runtime, Gateway, Memory, Identity, Policy, Evaluations, and AgentCore Observability.
- Experience with MCP, A2A, AWS SDKs, and enterprise tool integration.
- Experience with Terraform / Infrastructure-as-Code.
- Experience with Lambda, ECS, EKS, API Gateway, EventBridge, Step Functions, SQS/SNS, S3, Secrets Manager, CloudWatch, networking, VPC endpoints, and private connectivity.
- Experience with ServiceNow or other ITSM platforms and IT infrastructure / CloudOps / SRE / AIOps use cases.
- Experience supporting customer POCs, pilots, MVPs, production rollouts, and technical workshops.

Other Requirements

Qualifications

- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or related field.
- 4-7 years of overall software engineering, cloud engineering, or equivalent technical experience.
- At least 2 years of practical Generative AI / Agentic AI experience.
- Demonstrated experience delivering an AI, automation, or cloud solution into production.

Key Attributes

- Customer-oriented and comfortable working in customer environments.
- Strong ownership and bias for execution.
- Robust troubleshooting and problem-solving ability.
- Able to balance reusable platform capabilities with customer-specific requirements.
- Comfortable working across AI engineering, AWS cloud, integration, and operations.

Information at a Glance

Why HCLTech?

At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark.



All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion.

Copyright © 2026 HCL Technologies Limited

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📌 Track Manager (Support & Operations) (India)
🏢 HCLTech
📍 India