Finance Transformation Data/AIML Engineer

Finance Transformation Data/AIML Engineer

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

We are looking for an AI & Automation Engineer (Contractor) to join our Digital Transformation / Automation team and support the design, development, integration, and production deployment of enterprise AI and automation solutions.

The role will work closely with the Lead Automation Architect, business teams, data engineering teams, and enterprise technology teams to convert business requirements into scalable, secure, and production-ready solutions.

This is a hands-on engineering role. The ideal candidate should be comfortable owning development from requirements and technical design through testing, deployment, and production support.

Selected candidates will work under the direction of the internal team lead, who retains ownership of the solution roadmap, architecture approvals, prioritisation, and business stakeholder relationships.

Key Responsibilities

• Design and develop enterprise AI, GenAI, Agentic AI, ML, and automation solutions.
• Build applications and services using Python and modern API/framework technologies.
• Develop AI agents and workflows using LLMs, prompt engineering, tool/function calling, RAG, and enterprise data sources.
• Integrate solutions with enterprise applications like Databricks, SailPoint, Okta, Atlas etc.
• Develop and integrate solutions using Azure services, including Azure OpenAI and related cloud services.
• Work with Databricks datasets and data pipelines for AI/ML and analytical use cases. Having knowledge of ML based forecasting and different ML Models
• Support integration with enterprise platforms such as Salesforce, SAP, Anaplan, Power BI, ServiceNow, and other business systems, where required.
• Implement authentication and authorization using enterprise identity solutions such as Okta, Entra ID / Azure AD, OAuth, and role-based access controls.
• Perform unit testing, integration testing, regression testing, and support business UAT.
• Support deployment across Development, Test/UAT, and Production environments.
• Troubleshoot application, integration, infrastructure, and data issues.
• Follow enterprise standards for security, logging, monitoring, exception handling, source control, and deployment.
• Prepare required technical documentation including solution design, deployment instructions, support documentation, and test evidence.
• Work independently while providing clear progress updates, risks, dependencies, and blockers.
• Responsible for conducting advanced research in AI and machine learning. This includes staying up to date with the latest advancements in the field, exploring emerging technologies, and identifying opportunities to apply cutting-edge techniques to solve complex business problems.
• Tasked with designing and architecting AI solutions for complex problems. This involves analyzing business requirements, understanding constraints, and proposing appropriate machine learning models and algorithms.
• Responsible for considering scalability, performance, and maintainability while designing the solution.
• Provides technical guidance and mentorship to junior team members. This includes sharing best practices, reviewing code and designs, and helping team members overcome technical challenges. Participate in technical discussions and provide thought leadership within the organization.
• Works closely with stakeholders, such as product managers, data scientists, and business analysts, to understand their requirements and translate them into technical solutions. Collaborate with cross-functional teams to ensure alignment and successful AI and machine learning project implementation.
• Responsible for driving continuous improvement and innovation in the organization's AI and machine learning practices. This involves identifying areas of improvement, exploring new techniques or technologies, and promoting the adoption of best practices.
• Be involved in evaluating and integrating third-party tools or services that can enhance the capabilities of AI solutions.
• Facilitates design review sessions for your projects, ensuring alignment with project requirements and best practices.
• Mentor junior team members during review sessions.
• Collaborates closely with the engineering manager and team lead to refine and iterating on design and implementation strategies, providing constructive feedback to peers.
• Participates in and coordinates meetings, ensuring effective coordination and communication among team members.
• Independently prepares and delivers detailed presentations and reports to stakeholders, translating complex technical concepts into understandable terms for non-technical audiences.
• May be required to interpret and report data findings and maintain or update specific business intelligence tools, databases, dashboards, systems, or methods
• May be involved in the design and development of solutions to complex application problems, system administration issues, or network concerns, where applicable to the role.

Knowledge and Skills

• Deep understanding of machine learning algorithms, such as linear regression, decision trees, support vector machines, random forests,