Finance Transformation Data/AIML Engineer

Hewlett Packard Enterprise • Spring, TX

1d • $126,500 - $290,500 • Onsite

About The Position

Hewlett Packard Enterprise is seeking an AI & Automation Engineer for its Digital Transformation / Automation team. The role supports the design, development, integration, testing, deployment, and production support of enterprise AI and automation solutions. It works with the Lead Automation Architect, business teams, data engineering teams, and enterprise technology teams to turn business requirements into scalable, secure, production-ready solutions. This is a hands-on engineering role, with development ownership spanning requirements and technical design through deployment and production support. Selected candidates work under the direction of the internal team lead, who retains ownership of the solution roadmap, architecture approvals, prioritization, and business stakeholder relationships.

The engineer will develop enterprise AI, GenAI, agentic AI, machine learning, and automation solutions; build Python applications and services; create LLM-based agents and workflows; and integrate with enterprise data, identity, cloud, and business platforms. The role also includes advanced AI and machine learning research, architecture and design for complex problems, mentoring junior engineers, design reviews, stakeholder collaboration, and continuous improvement of AI and machine learning practices.

The position is designed as onsite, with an expectation of primarily working from an HPE office. HPE describes its workplace as inclusive and offers a comprehensive suite of health, financial, and emotional wellbeing benefits, as well as personal and professional development programs. The stated annual base salary range for Texas in the United States is USD 126,500–290,500; variable incentives may also be offered.

Requirements

• At least 5 years of overall software engineering, automation, data, or AI development experience.
• At least 3 years of strong Python development experience.
• Strong hands-on experience with Python.
• Strong understanding of REST APIs and system integrations.
• Demonstrable hands-on experience delivering enterprise applications or automation solutions, including deploying solutions to cloud servers.
• Experience with Git, GitHub, or equivalent source-control tools.
• Experience with CI/CD and production deployment practices.
• Hands-on experience developing applications based on Generative AI or LLMs.
• Experience with prompt engineering and structured LLM outputs.
• Experience with RAG and enterprise knowledge retrieval.
• Understanding of agent, tool, and function-calling concepts.
• Experience with LLM evaluation, guardrails, error handling, and hallucination mitigation.
• Experience with Azure OpenAI or comparable enterprise LLM platforms.
• Experience working with Microsoft Azure.
• Experience with Azure Container Apps, App Service, or Functions.
• Experience with Docker and container-based application deployment.
• Deep understanding of machine learning algorithms, including linear regression, decision trees, support vector machines, random forests, deep learning models, and reinforcement learning; model selection, hyperparameter tuning, and model-performance evaluation using appropriate metrics.
• Strong foundation in mathematics and statistics, including linear algebra, calculus, probability theory, and statistical concepts.
• Proficiency in Python, R, or Java, along with production-level coding experience and familiarity with software engineering best practices, version control, and software development methodologies.
• Advanced knowledge and experience in deep learning, including neural network architectures such as CNNs, RNNs, and transformers, and techniques such as transfer learning, generative models, and deep learning optimization algorithms.
• Ability to conduct research, explore emerging technologies, and identify opportunities to apply current AI and machine learning techniques to complex problems.
• Ability to provide technical leadership, mentorship, and guidance to junior team members.
• Excellent communication skills for effective collaboration with cross-functional teams and stakeholders, and strong problem-solving and critical-thinking abilities.
• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline; equivalent strong industry experience may also be considered.

Nice To Haves

• Recent hands-on exposure to GenAI/LLM-based application development is strongly preferred.
• Knowledge of libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras.
• Experience with agentic AI frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent.
• Knowledge of ML-based forecasting and different ML models.

Responsibilities

• Design and develop enterprise AI, GenAI, agentic AI, machine learning, and automation solutions.
• Build applications and services using Python and modern API and framework technologies.
• Develop AI agents and workflows using LLMs, prompt engineering, tool/function calling, RAG, and enterprise data sources.
• Integrate solutions with enterprise applications and platforms, including Databricks, SailPoint, Okta, Atlas, Salesforce, SAP, Anaplan, Power BI, and ServiceNow, where required.
• 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, including knowledge of ML-based forecasting and different ML models.
• Implement authentication and authorization using enterprise identity solutions such as Okta, Entra ID / Azure AD, OAuth, and role-based access controls.
• Perform unit, integration, and 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 technical documentation, including solution designs, deployment instructions, support documentation, and test evidence.
• Provide progress updates and communicate risks, dependencies, and blockers while working independently.
• Conduct advanced research in AI and machine learning, follow developments in the field, explore emerging technologies, and identify opportunities to apply state-of-the-art techniques to business problems.
• Analyze business requirements and constraints, and design and architect appropriate AI solutions, models, and algorithms with attention to scalability, performance, and maintainability.
• Provide technical guidance and mentorship to junior team members, share best practices, review code and designs, and help resolve technical challenges.
• Collaborate with product managers, data scientists, business analysts, stakeholders, and cross-functional teams to translate requirements into technical solutions and support successful implementation.
• Drive continuous improvement and innovation in AI and machine learning practices, and evaluate and integrate third-party tools or services that can improve AI solutions.
• Facilitate design review sessions and mentor junior team members during reviews.
• Collaborate with the engineering manager and team lead to refine design and implementation strategies and provide constructive feedback to peers.
• Participate in and coordinate meetings to support team coordination and communication.
• Prepare and deliver detailed presentations and reports, explaining complex technical concepts to non-technical audiences.
• When required, interpret and report data findings and maintain or update business intelligence tools, databases, dashboards, systems, or methods.
• Where applicable, contribute to solutions for complex application problems, system administration issues, or network concerns.

Benefits

• Comprehensive suite of benefits supporting physical, financial, and emotional wellbeing.
• Personal and professional development programs to support career goals.
• Variable incentives may also be offered in addition to base salary.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior