Applied Ai Engineer

Applied AI Engineer

This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE office.

Job Description:

HPE Financial services is where we help organizations create the investment they need for digital transformation, in an innovative and sustainable way. We partner with customers across their entire IT asset portfolio from edge to cloud to end-user. Unique to each client’s aspirations and size, our financial and asset management solutions are anchored by best-in-class tech upcycling services. Join us redefine what’s next for you.

Role Summary
The Applied AI Engineer is an individual contributor role that applies developed subject matter knowledge in AI, data science, and automation to develop, sustain and iterate reliable solutions on agentic AI systems and conversational AI products, integrating leading LLMs — including but lot limited to Anthropic Claude, OpenAI GPT, and Microsoft Copilot — into real-world business workflows. The role involves solving common and moderately complex technical issues, exercising independent judgment in selecting methods and tools, and collaborating with peers and senior team members to achieve project objectives. The ideal candidate brings a strong technical foundation and a scientist's appetite for experimentation. The ideal candidate will be comfortable working across the full AI delivery stack from data wrangling and model evaluation to prompt engineering, API integration, and lightweight automation.

What you'll do:

• Apply established AI and data science techniques to design, build, test, and support AI-enabled solutions aligned to business requirements.

• Solve common and occasionally complex technical problems related to machine learning models, LLM-based solutions, agentic workflows, and data pipelines, using sound engineering judgment.

• Recommend alternative technical approaches, model configurations, or solution designs when standard methods are insufficient or suboptimal.

• Contribute across the solution lifecycle including experimentation, development, validation, documentation, and deployment support.

• Perform data analysis, feature preparation, and model evaluation to support AI-driven use cases.

• Develop clear technical documentation, dashboards, or summaries to communicate results to technical and non-technical stakeholders

• Provide technical assistance, code reviews, or day-to-day guidance to junior developers, interns, or new team members when required

Agentic & Conversational AI

• Design and develop multi-step agentic AI pipelines using orchestration frameworks such as LangChain, LangGraph, AutoGen, or Semantic Kernel.

• Build and maintain conversational AI assistants and chatbots, including retrieval-augmented generation (RAG) architectures.

• Engineer, test, and refine prompts for Claude, GPT, and Copilot; implement few-shot, chain-of-thought, and structured output strategies.

• Integrate LLMs into custom AI products via REST APIs, SDKs, and tool-use / function-calling interfaces

Data Science & Analytics

• Perform exploratory data analysis, feature engineering, and statistical modelling to derive business insights.

• Build and evaluate machine learning models (classification, regression, NLP) and document results clearly for technical and non-technical stakeholders.

• Maintain clean, versioned datasets and support data pipeline tasks in collaboration with data engineering teams

Reporting & Visualization

• Develop lightweight dashboards and reports using Power BI, Tableau, or Python-based visualization libraries

• Translate analytical findings into clear visual narratives for business audiences.

RPA & Workflow Automation

• Support the integration of robotic process automation (RPA) solutions on platforms such as UiPath and Power Automate, into end to end AI products

• Identify repetitive manual processes and propose AI-assisted automation enhancements

Experimentation & Innovation

• Continuously evaluate emerging AI tools, frameworks, and research papers; propose and drive experiments to show and validate the capabilities

• Document learnings, support in maintaining internal knowledge repositories, and contribute to team capability building.

What you need to bring:

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.

• 4 – 5 years of hands-on experience in AI/ML development, data science, or software engineering roles.

• Demonstrable experience working with at least one major LLM API (Claude, GPT, Gemini, or equivalent).

• Portfolio or project evidence of building agentic or conversational AI systems is strongly preferred.

• Exposure to RPA tools and BI reporting platforms will be advantageous.

Technical Skills

• LLM Integration - Anthropic Claude API, OpenAI GPT API, Microsoft Copilot / Azure OpenAI; prompt engineering, function-calling, tool-use, structured outputs

• Agentic Frameworks - LangChain, LangGraph, AutoGen, Semantic Kernel; agent orchestration, tool routing, memory management

• Programming - Python (primary), SQL; familiarity with JavaScript/TypeScript a plus

• MLOps & Dev Tools - Git/GitHub, Docker basics, REST APIs, FastAPI or Flask for API serving; Jupyter Notebooks

• Reporting & BI - Power BI, QlikVue/ QlikSense

• RPA Automation -UiPath or Microsoft Power Automate

• Databases - Databricks, Azure SQL, SQL, Collibra

Accountability, Accountability, Action Planning, Active Learning, Active Listening, Agile Methodology, Agile Scrum Development, Analytical Thinking, Bias, Coaching, Creativity, Critical Thinking, Cross-Functional Teamwork, Data Analysis Management, Data Collection Management (Inactive), Data Controls, Design, Design Thinking, Empathy, Follow-Through, Group Problem Solving, Growth Mindset, Intellectual Curiosity (Inactive), Long Term Planning, Managing Ambiguity {+ 5 more}

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.

#india

Job:

Engineering

Job Level:

TCP_03

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

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