AI/ML Engineer

AI/ML Engineer This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office. Who We Are: Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE. Job Description: Job Family Definition: Develops and programs integrated software algorithms to structure, analyze and leverage structured and unstructured data in product and systems applications. Can work with large scale computing frameworks, data analysis systems, and modeling environments. Uses machine learning and statistical modeling techniques to improve product/system performance, data management, quality, and accuracy. Formulates descriptive, diagnostic, predictive and prescriptive insights/algorithms and translates technical specifications into code. Applies, optimizes and scales deep learning technologies and algorithms to give computers the capability to visualize, learn and respond to complex situations. Documents procedures for installation and maintenance, completes programming, performs testing and debugging, defines and monitors performance metrics. Contributes to the success of HPE by translating customer requirements and industry trends into AI/ML products, solutions, and systems improvement projects. Management Level Definition: Contributions include applying intermediate level of subject matter expertise to solve common technical problems. Acts as an informed team member providing analysis of information and recommendations for appropriate action. Works independently within an established framework and with moderate supervision. What you'll do: Designs, develops, and orchestrates advanced Generative AI applications with a specific focus on autonomous agents and multi-agent systems for our enterprise-grade network technology and autonomous platform. Leverages large language models (LLMs) to create reasoning engines that interact with external tools, APIs, and structured data. Specializes in building stateful, cyclic AI workflows using LangGraph to solve complex, non-linear problems in enterprise network. Translates high-level product requirements into robust Python code, bridging the gap between stochastic LLM outputs and deterministic software systems. Implements Retrieval-Augmented Generation (RAG), optimizes prompt engineering strategies, and deploys scalable agentic architectures that can visualize, plan, and execute multi-step tasks. Agentic Architecture Design: Design and implement stateful, multi-agent workflows using LangGraph. Define nodes, edges, and conditional logic to create agents capable of loops, self-correction, and human-in-the-loop interactions. GenAI Application Development: Develop end-to-end GenAI applications in Python, utilizing frameworks like LangChain and LlamaIndex to integrate LLMs (e.g., GPT-4, Claude, Llama 3) with enterprise data and APIs. Tool & Function Calling: Engineer robust "tools" and function-calling interfaces that allow agents to interact with internal databases, perform web searches, or execute code to complete tasks. Performance Optimization: Evaluate and improve agent performance. Move beyond basic accuracy metrics to measure "agent trajectory" quality, token usage efficiency, latency, and success rates in multi-step reasoning tasks. Collaboration & Integration: Collaborate with software engineers to expose agents via APIs (e.g., FastAPI) and integrate them into existing product ecosystems. Explain agent decision-making processes (observability) to non-technical stakeholders. Code Quality & Review: Contribute to design review sessions, specifically focusing on the maintainability of complex graph structures and state management. Provide feedback to peers on Python best practices and asynchronous programming. Prompt Engineering & Fine-Tuning: Design sophisticated system prompts and manage prompt versioning. Occasionally fine-tune Small Language Models (SLMs) for specific domain tasks where latency or cost is a constraint. Prototyping to Production: Rapidly prototype new agent concepts in stand-ups and move successful experiments to production-grade code, handling error recovery and guardrails against hallucination. What you need to bring: Education and Experience Required Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field. Master’s degree preferred. Typically 2-4 years of total software or data engineering experience. Specific Requirement: At least 1 year of hands-on experience working with Generative AI, or building applications with LangChain/LangGraph. Core Technical Skills: Advanced Python: Strong proficiency in Python is non-negotiable, particularly with asynchronous programming (asyncio), Pydantic (for data validation), and typing. GenAI Frameworks: Deep practical knowledge of LangGraph (for graph-based flows) and LangChain. Familiarity with DSPy or AutoGen is a plus. LLM Orchestration: Understanding of Context Windows, Tokenization, Temperature, and the mechanics of Chat APIs (OpenAI, Anthropic, HuggingFace). Agentic Skills: Graph Theory & Logic: Ability to visualize and implement business logic as directed cyclic graphs (nodes, edges, conditional jumps). NoSQL Databases: Experience with Elasticsearch, redis or vector stores such as Pinecone, Milvus, Qdrant, or PGVector. Foundational Skills: Software Engineering: Proficient with Git, Docker, and CI/CD pipelines. Experience building and consuming RESTful APIs. Math & Stats: Solid understanding of linear algebra (embeddings) and probability as it relates to model sampling and decision-making. Communication: Ability to demystify "AI Magic" and explain the limitations (e.g., hallucinations) and capabilities of agentic systems to product managers and business stakeholders. Additional Skills: Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security-First Mindset What We Can Offer You: Health & Wellbeing We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing. Personal & Professional Development We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division. Unconditional Inclusion We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. Let's Stay Connected: Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE. #india #networking Job: Engineering Job Level: TCP_02 HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity. Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities. 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