Track Manager - Apache Kafka, Windows PowerShell

HCL Technologies Limited; Bengaluru; On-site; INR 5,000,000 - 7,500,000; Full time

Job summary

HCL Technologies Limited in Bengaluru seeks a Lead Engineer – Artificial Intelligence (AI) to design, develop, integrate, and operationalize AI solutions. The role emphasizes Python engineering, Generative AI, LLMs and agentic AI, collaborating with engineering, security and data teams to deliver scalable AI-powered services.

The ideal candidate will build AI components, REST APIs, vector stores, and orchestration workflows, while applying best practices for testing, observability and production

Qualifications

• Strong hands-on Python with OOP, data structures, REST API development and async programming.
• Experience with FastAPI/Flask, Pydantic, Pandas/NumPy, PyTest, and ML/LLM SDKs.
• Hands-on knowledge of LLMs, prompt engineering, RAG, embeddings and vector databases.
• Experience with platforms/models such as Azure OpenAI/OpenAI, Anthropic, Gemini or open-source LLMs.
• Agentic AI: AI agents, tool-enabled agents, orchestration and multi-step workflows.

Responsibilities

• Design, develop, test, and maintain AI-powered applications and services using Python.
• Build solutions leveraging Generative AI, LLMs, Agentic AI, ML, NLP, RAG, and automation.
• Develop reusable Python modules, APIs, services, connectors, and AI components.
• Build AI agents capable of interacting with enterprise apps, APIs, databases, and automation platforms.
• Develop orchestration workflows integrating AI models with existing systems and processes.
• Apply software engineering best practices including modular design, version control, testing, documentation, logging, and error handling.
• Perform code reviews and contribute to engineering standards and reusable patterns.
• Translate requirements into technical designs and implementation approaches.

Skills

OOP

Data structures

REST API

Async programming

Error handling

Unit testing

Dependency management

Code optimization

Design patterns

Git workflows

FastAPI

Flask

Pydantic

Pandas

NumPy

PyTest

AI/ML SDKs

LLMs

RAG

Agentic AI

Azure OpenAI/OpenAI

Anthropic

Open-source LLMs

Tools

FastAPI

Flask

Job description

Track Manager - Apache Kafka, Windows PowerShell Track Manager - Apache Kafka, Windows PowerShell India Job Description Track Manager - Apache Kafka, Windows PowerShell Bengaluru, Karnataka

Job Summary

We are seeking an experienced and hands‑on Lead Engineer – Artificial Intelligence (AI) to design, develop, integrate, and operationalize AI solutions across the organization. The role will focus on translating business and operational requirements into production‑ready AI applications, with a strong emphasis on Python engineering, Generative AI, Large Language Models (LLMs), Agentic AI, Machine Learning, Retrieval Augmented Generation (RAG), APIs, and intelligent automation. The successful candidate will work closely with engineering, operations, architecture, security, service management, tooling, data, and business teams to develop scalable and secure AI solutions that improve operational efficiency, automate repetitive activities, enhance decision‑making, and improve service delivery. This is a hands‑on technical role requiring strong software engineering fundamentals, advanced Python programming skills, practical experience building AI applications, and the ability to technically guide engineers through design and implementation.

• Design, develop, test, and maintain AI‑powered applications and services using Python.
• Build solutions leveraging Generative AI, LLMs, Agentic AI, Machine Learning, NLP, RAG, and intelligent automation.
• Develop reusable Python modules, APIs, services, connectors, and AI components.
• Build AI agents capable of interacting with enterprise applications, APIs, databases, knowledge repositories, and automation platforms.
• Develop orchestration workflows integrating AI models with existing enterprise systems and operational processes.
• Apply software engineering best practices including modular design, version control, automated testing, documentation, logging, and error handling.
• Perform code reviews and contribute to engineering standards and reusable development patterns.
• Translate functional and business requirements into technical designs and implementation approaches.
• Develop Proof of Concepts (PoCs), prototypes and Minimum Viable Products (MVPs) to validate AI use cases.
• Contribute to solution architecture covering application components, APIs, AI models, data sources, vector stores, integrations, authentication, and deployment.
• Collaborate with enterprise architecture, security, infrastructure, cloud, data, and operations teams.
• Support the transition of successful prototypes into scalable production solutions.
• Troubleshoot complex application, integration, model, and performance issues.
• Develop high‑quality and maintainable Python applications for AI, automation and integration use cases.
• Build REST APIs and backend services using appropriate Python frameworks.
• Integrate applications with enterprise platforms through REST APIs, SDKs, databases, messaging systems and other interfaces.
• Apply object‑oriented programming, asynchronous programming, concurrency and appropriate software design patterns.
• Implement unit testing, integration testing and automated validation.
• Use Git‑based development practices including branching, pull requests, code reviews and CI/CD.
• Optimize Python applications for reliability, scalability and performance.
• Support deployment, monitoring, troubleshooting and lifecycle management of AI solutions.
• Implement appropriate application and model observability including logging, tracing, metrics and error handling.
• Develop mechanisms to monitor AI solution quality, latency, usage, reliability and cost.
• Support model and prompt versioning, testing and controlled releases.
• Work with platform and DevOps teams to automate build, deployment and configuration processes.
• Ensure AI solutions are supportable and maintainable within enterprise production environments.
• Implement AI solutions in accordance with organizational security, privacy, compliance and Responsible AI.

Key Responsibilities

We are seeking an experienced and hands‑on Lead Engineer – Artificial Intelligence (AI) to design, develop, integrate, and operationalize AI solutions across the organization. The role will focus on translating business and operational requirements into production‑ready AI applications, with a strong emphasis on Python engineering, Generative AI, Large Language Models (LLMs), Agentic AI, Machine Learning, Retrieval Augmented Generation (RAG), APIs, and intelligent automation. The successful candidate will work closely with engineering, operations, architecture, security, service management, tooling, data, and business teams to develop scalable and secure AI solutions that improve operational efficiency, automate repetitive activities, enhance decision‑making, and improve service delivery. This is a hands‑on technical role requiring strong software engineering fundamentals, advanced Python programming skills, practical experience building AI applications, and the ability to technically guide engineers through design and implementation.

• Design, develop, test, and maintain AI‑powered applications and services using Python.
• Build solutions leveraging Generative AI, LLMs, Agentic AI, Machine Learning, NLP, RAG, and intelligent automation.
• Develop reusable Python modules, APIs, services, connectors, and AI components.
• Build AI agents capable of interacting with enterprise applications, APIs, databases, knowledge repositories, and automation platforms.
• Develop orchestration workflows integrating AI models with existing enterprise systems and operational processes.
• Apply software engineering best practices including modular design, version control, automated testing, documentation, logging, and error handling.
• Perform code reviews and contribute to engineering standards and reusable development patterns.
• Translate functional and business requirements into technical designs and implementation approaches.
• Develop Proof of Concepts (PoCs), prototypes and Minimum Viable Products (MVPs) to validate AI use cases.
• Contribute to solution architecture covering application components, APIs, AI models, data sources, vector stores, integrations, authentication, and deployment.
• Collaborate with enterprise architecture, security, infrastructure, cloud, data, and operations teams.
• Support the transition of successful prototypes into scalable production solutions.
• Troubleshoot complex application, integration, model, and performance issues.
• Develop high‑quality and maintainable Python applications for AI, automation and integration use cases.
• Build REST APIs and backend services using appropriate Python frameworks.
• Integrate applications with enterprise platforms through REST APIs, SDKs, databases, messaging systems and other interfaces.
• Apply object‑oriented programming, asynchronous programming, concurrency and appropriate software design patterns.
• Implement unit testing, integration testing and automated validation.
• Use Git‑based development practices including branching, pull requests, code reviews and CI/CD.
• Optimize Python applications for reliability, scalability and performance.
• Support deployment, monitoring, troubleshooting and lifecycle management of AI solutions.
• Implement appropriate application and model observability including logging, tracing, metrics and error handling.
• Develop mechanisms to monitor AI solution quality, latency, usage, reliability and cost.
• Support model and prompt versioning, testing and controlled releases.
• Work with platform and DevOps teams to automate build, deployment and configuration processes.
• Ensure AI solutions are supportable and maintainable within enterprise production environments.
• Implement AI solutions in accordance with organizational security, privacy, compliance and Responsible AI.

Skill Requirements

Mandatory Technical Skills Python Strong hands‑on experience with Python is essential, including:

• Object‑oriented programming
• Data structures and algorithms
• REST API development and integration
• Asynchronous programming
• Error handling and logging
• Unit and integration testing
• Package and dependency management
• Code optimization
• Software design patterns
• Git‑based development

Experience with commonly used Python libraries and frameworks such as:

• FastAPI / Flask
• Pydantic
• Pandas / NumPy
• PyTest
• AI/ML and LLM SDKs/frameworks as appropriate

Generative AI & LLMs Hands‑on knowledge of:

• Large Language Models
• Prompt engineering
• Structured outputs and tool/function calling
• Retrieval Augmented Generation (RAG)
• EmbeddingsVector databases
• Semantic search
• Context management
• Model evaluation
• LLM integration patterns

Experience with platforms/models such as:

• Azure OpenAI / OpenAI
• Anthropic
• Google Gemini
• Open‑source LLMs

Agentic AI Practical understanding of:

• AI agents
• Tool/API‑enabled agents
• Agent orchestration
• Multi‑step AI workflows
• Agent memory and context
• Human‑in‑the‑loop workflows
• Guardrails and controlled execution

Experience with relevant agentic frameworks or SDKs is advantageous.

Other Requirements

Mandatory Technical Skills Python Strong hands‑on experience with Python is essential, including:

• Object‑oriented programming
• Data structures and algorithms
• REST API development and integration
• Asynchronous programming
• Error handling and logging
• Unit and integration testing
• Package and dependency management
• Code optimization
• Software design patterns
• Git‑based development

Experience with commonly used Python libraries and frameworks such as:

• FastAPI / Flask
• Pydantic
• Pandas / NumPy
• PyTest
• AI/ML and LLM SDKs/frameworks as appropriate

Generative AI & LLMs Hands‑on knowledge of:

• Large Language Models
• Prompt engineering
• Structured outputs and tool/function calling
• Retrieval Augmented Generation (RAG)
• Embeddings
• Vector databases
• Semantic search
• Context management
• Model evaluation
• LLM integration patterns

Experience with platforms/models such as:

• Azure OpenAI / OpenAI
• Anthropic
• Google Gemini
• Open‑source LLMs

Agentic AI Practical understanding of:

• AI agents
• Tool/API‑enabled agents
• Agent orchestration
• Multi‑step AI workflows
• Agent memory and context
• Human‑in‑the‑loop workflows
• Guardrails and controlled execution

Experience with relevant agentic frameworks or SDKs is advantageous.

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 $14.8billion.