Platform Engineer II

Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Artificial Intelligence · Cloud Engineering · DevOps

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In short

As an Agentic AI Engineer II in the Cloud Native COE, you will build GenAI and agentic AI components using Python and/or Java. This role involves coding LLM-based agents, tool integrations, and RAG pipelines, and bringing them to production-ready quality, suitable for engineers with 2-3 years of experience.

Responsibilities

Develop, test and debug agentic AI and GenAI components, such as LLM agents, tool/function calling and RAG pipelines.
Design and optimize prompts for different LLMs, and evaluate model outputs.
Integrate LLM APIs (e.g., OpenAI, Azure OpenAI, AWS Bedrock) and vector databases with enterprise data sources.
Build and maintain POCs, demos and reusable code components.
Implement guardrails, logging and monitoring for AI services.
Deploy and run services on cloud platforms (AWS, Azure or Google Cloud) using CI/CD pipelines and DevOps tools.
Prepare technical documentation, code walkthroughs and demo notes.
Participate in code reviews, sprint ceremonies and internal knowledge-sharing sessions.

Requirements

Hands-on Python and/or Java experience.
Working experience with TensorFlow or PyTorch.
Proficiency in GenAI frameworks and libraries such as OpenAI.
Prompt engineering skills – designing and optimizing prompts for various AI models.
Proficiency in core ML concepts and algorithms.
Knowledge of deep learning techniques and neural networks.
Understanding of NLP techniques and tools, including tokenization, embeddings, transformers and language models.
Knowledge of vector databases and LLMs, and of integrating applications with them.
Experience working with cloud services on AWS, Azure or Google Cloud.
Knowledge of DevOps practices and tools (e.g., Git, CI/CD pipelines, Docker).
Strong communication and articulation skills.
Ability to identify issues and come up with effective solutions.
Enthusiasm to learn new technologies; a quick learner who can learn on the job.
2–3 years of hands-on coding experience in Python and/or Java.
Working experience with ML/DL frameworks such as TensorFlow or PyTorch.
Hands-on experience using GenAI frameworks and libraries such as OpenAI, and in designing and optimizing prompts for LLMs.
Experience working with cloud services on AWS, Azure or Google Cloud.

Desired Qualifications

Exposure to agentic AI frameworks such as LangChain, LangGraph, CrewAI or MCP.
Experience building REST APIs (e.g., FastAPI, Flask or Spring Boot).
Working knowledge of SQL and NoSQL databases.
Bachelor’s or master’s degree in Engineering, Computer Science, or a related field.
GenAI or cloud certifications (AWS, Azure, GCP) are an advantage but not mandatory.

Benefits

Opportunity to learn and deepen skills in GenAI, agentic AI and cloud-native engineering on the job.
Work with senior architects and technical leads.
Opportunity to work with leading LLM APIs and cloud platforms.
Stay current with new GenAI, agentic AI and cloud-native tools and frameworks.
Share learnings with the team.
Pick up new technologies quickly and apply them on the job.

Skills

PythonJavaTensorFlowPyTorchOpenAIPrompt EngineeringMachine LearningDeep LearningNLPVector DatabasesLLMAWSAzureGoogle CloudDevOpsGitCI/CDDockerREST APIsFastAPIFlaskSpring BootSQLNoSQLLangChainLangGraphCrewAIMCP

#AI#Machine Learning#Deep Learning#NLP#GenAI#Agentic AI#LLM#Cloud#Platform Engineering#DevOps#Python#Java#AWS#Azure#GCP

About HCLTech

Supercharging progress through technology and innovation

HCLTech is a global technology company, home to 219,000+ people across 54 countries, delivering industry-leading capabilities centered around digital, engineering and cloud, 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 September 2022 totaled $12.1 billion. To learn how we can supercharge progress for…

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