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Hewlett Packard Enterprise

Builds servers, networking and private cloud

Finance Transformation Data/AIML Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeSpring, TX, USA

About the Job

Requirements

  • A 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.
  • 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.
  • Experience developing enterprise applications or automation solutions, including deployment of solutions to cloud servers.
  • Git, GitHub, or equivalent source-control experience.
  • Experience with continuous integration/continuous deployment (CI/CD) and production deployment practices.
  • Hands-on experience with generative AI or large language model (LLM)-based application development.
  • Experience with prompt engineering and structured LLM outputs.
  • Experience with retrieval-augmented generation (RAG) and enterprise knowledge retrieval.
  • Knowledge 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 with Microsoft Azure.
  • Experience with an agentic AI framework such as LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent.
  • 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 such as neural networks, and reinforcement learning; proficiency in model selection, hyperparameter tuning, and evaluation using appropriate metrics.
  • A strong foundation in mathematics and statistics, including linear algebra, calculus, probability theory, and statistical concepts.
  • Proficiency in Python, R, or Java; production-level coding experience; familiarity with software engineering best practices, version control systems, and software development methodologies.
  • Advanced knowledge and experience in deep learning, including neural network architectures such as convolutional neural networks, recurrent neural networks, and transformers, and techniques such as transfer learning, generative models, and 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 and collaborate with cross-functional teams and stakeholders.
  • Strong problem-solving and critical-thinking abilities to guide projects, make strategic decisions, and address complex technical challenges.

Responsibilities

  • Design and develop enterprise AI, generative AI, 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 and function calling, RAG, and enterprise data sources.
  • Integrate solutions with enterprise applications such as Databricks, SailPoint, Okta, and Atlas.
  • Develop and integrate solutions using Azure services, including Azure OpenAI and related cloud services.
  • Work with Databricks datasets and data pipelines for AI, machine learning, and analytical use cases, including machine-learning-based forecasting and models.
  • Support integration with Salesforce, SAP, Anaplan, Power BI, ServiceNow, and other business systems as required.
  • Implement authentication and authorization using enterprise identity solutions such as Okta and Entra ID/Azure AD, OAuth, and role-based access controls.
  • Perform unit, integration, and regression testing, and support business user acceptance testing (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 design, deployment instructions, support documentation, and test evidence.
  • Work independently and provide progress updates about risks, dependencies, and blockers.
  • Conduct advanced research in AI and machine learning, stay current with developments, explore emerging technologies, and identify opportunities to apply techniques to business problems.
  • Analyze business requirements and constraints and design and architect AI solutions, selecting appropriate machine learning models and algorithms while considering 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.
  • Work with product managers, data scientists, business analysts, and other stakeholders to understand requirements and translate them into technical solutions; collaborate across teams to implement AI and machine learning projects.
  • Drive continuous improvement and innovation in AI and machine learning practices, identify areas for improvement, and promote adoption of best practices.
  • Evaluate and integrate third-party tools or services that can enhance AI solutions.
  • Facilitate design review sessions for projects 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 coordination and communication among team members.
  • Prepare and deliver detailed presentations and reports to stakeholders, explaining technical concepts to non-technical audiences.
  • Interpret and report data findings and maintain or update business intelligence tools, databases, dashboards, systems, or methods as required.
  • Contribute to designing and developing solutions to complex application problems, system administration issues, or network concerns where applicable.

Desired Qualifications

  • Recent hands-on exposure to generative AI or LLM-based application development is strongly preferred.
  • Knowledge of libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras.

About the Company

Hewlett Packard Enterprise

Builds servers, networking and private cloud

Hewlett Packard Enterprise sells servers, storage, networking and hybrid cloud software to large companies, governments and service providers. Its GreenLake platform lets customers run on-premises hardware as a metered cloud service, and its Cray supercomputers run national lab and AI training workloads. The networking business, built on Aruba and Juniper Networks, supplies campus, data-center and routing equipment. Revenue comes from hardware sales, multiyear support contracts, financing and subscriptions. The company traces its roots to Hewlett-Packard, founded in 1939, became a separate public company in 2015 and is headquartered in Houston, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Houston, TX
Founded
1939

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