Credit Acceptance Corporation
San Francisco, California
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Credit Acceptance makes vehicle ownership possible for consumers other lenders decline, through a dealer network, an originations and servicing platform, and pricing and decisioning models refined over decades. The technology estate underneath this business was built project by project over a long period, and modernizing it is the largest engineering opportunity at the company. As the Distinguished Engineer, you are the senior-most individual contributor in Technology, reporting directly to the Chief Technology Officer. You will set the multi-year technical strategy for the company while staying close enough to the code and systems to remain credible - this is not an architect role that reviews designs from a distance, nor a strong engineer role that goes deep in a single domain. Two things sit at the center of the job: the target architecture for the enterprise, and the architecture for running AI agents across it. You will not own a team; you will own the hardest technical problems the company has, and get them resolved by convincing the people who do own the teams. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated . click apply for full job details
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Credit Acceptance makes vehicle ownership possible for consumers other lenders decline, through a dealer network, an originations and servicing platform, and pricing and decisioning models refined over decades. The technology estate underneath this business was built project by project over a long period, and modernizing it is the largest engineering opportunity at the company. As the Distinguished Engineer, you are the senior-most individual contributor in Technology, reporting directly to the Chief Technology Officer. You will set the multi-year technical strategy for the company while staying close enough to the code and systems to remain credible - this is not an architect role that reviews designs from a distance, nor a strong engineer role that goes deep in a single domain. Two things sit at the center of the job: the target architecture for the enterprise, and the architecture for running AI agents across it. You will not own a team; you will own the hardest technical problems the company has, and get them resolved by convincing the people who do own the teams. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated . click apply for full job details
HP
Spring, Texas
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Principal Enterprise Integration and Platform Native AI Description - Role Summary We are seeking an exceptional Principal Enterprise Integration & AI to lead HP's enterprise integration and AI architecture at global scale. This role serves as a technical authority, strategic thought leader, and innovation driver , responsible for shaping HP's integration fabric, API economy, and AI enablement strategy across Digital Tech. The Distinguished Engineer will define long-term architecture vision, influence enterprise-wide technology decisions, and ensure scalable, secure, and AI-ready platforms that accelerate business outcomes. This role operates at the intersection of integration, APIs, data, and AI , driving foundational capabilities that power HP's digital transformation and agentic AI future. Key Responsibilities API & AI-First API Strategy and Governance Define and lead HP's AI-first API strategy , ensuring all enterprise APIs are discoverable, reusable, and optimized for machine and agent consumption Institutionalize the API-as-a-Product operating model, with clear ownership, lifecycle governance, and measurable business value Own and enforce enterprise-wide API governance standards, covering design, lifecycle, security, and AI readiness Define and operationalize the AI-Ready API Framework , including automated governance gates to ensure production readiness Enable HP's Unified API & Agentic AI Strategy , positioning APIs as the foundation for enterprise AI adoption Establish standards for emerging integration paradigms, including event-driven architectures and MCP (Model Context Protocol) Platform AI Enablement & Governance Orchestrate AI enablement and adoption across strategic platforms (SAP, ServiceNow, Adobe, MuleSoft, NOVA) Own the enterprise AI/ML governance process, including AI board reviews, privacy, risk, and cybersecurity compliance Evaluate and guide platform-native AI capabilities to ensure alignment with enterprise architecture and compliance requirements Lead cross-functional AI enablement initiatives to drive consistent adoption and measurable business outcomes Align platform AI initiatives with enterprise prioritization frameworks (e.g., Digital AI Nerve Center) Evaluate AI tooling, vendor solutions, and partner ecosystems for alignment with integration and platform strategy Enable AI-driven SDLC adoption for partner ecosystems (e.g., NOVA vendors), including onboarding, compliance, and knowledge integration Lead/ support key tech initiatives Lead evaluation of new and emerging tech, conduct POC, and lay down path for adoption. Lead the EPS AI initiatives through AI/ML review board and cyber approval process. Partner with Applied AI teams for knowledge sharing of Enterprise AI initiatives Coach and mentor teams in their AI journey Improve reuse, reduce duplication, and strengthen governance via API-as-a-product discipline Enable scalable, enterprise-grade AI products (e.g., IBDF, AIOps) delivering measurable business value Qualifications & Experience 10+ years of experience in enterprise architecture, integration, and platform engineering Proven track record defining and implementing enterprise integration strategies and API ecosystems at scale Deep expertise in integration patterns (event-driven, messaging, APIs, microservices) and cloud-native architectures Experience leading AI/ML enablement, governance, and platform integration in large enterprises Strong understanding of enterprise platforms (SAP, ServiceNow, Adobe, MuleSoft) and their AI capabilities Demonstrated ability to influence executive stakeholders and drive cross-functional alignment Recognized as a thought leader and technical authority , with experience mentoring senior architects and engineers Leadership Expectations Act as a trusted advisor to executive leadership on enterprise architecture and AI strategy Drive innovation by identifying emerging technologies and translating them into enterprise capabilities Mentor and elevate the technical community, fostering architectural excellence across HP Represent HP externally with partners, customers, and industry forums as a leader in integration and AI Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. Typically has 10+ years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. Preferred Certifications Programming Language/s Certification (Java, C++, Python, JavaScript, or similar) Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API) • Automation • C++ (Programming Language) • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) Cross-Org Skills • Effective Communication • Results Orientation • Learning Agility • Digital Fluency • Customer Centricity Impact & Scope Impacts multiple functions and influences long-term strategic direction across multiple disciplines or areas of HP. Complexity Invents, develops and introduces new methods and techniques that impact multiple disciplines and work groups. Pay & Benefits The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave US benefits overview The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Disclaimer This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Principal Enterprise Integration and Platform Native AI Description - Role Summary We are seeking an exceptional Principal Enterprise Integration & AI to lead HP's enterprise integration and AI architecture at global scale. This role serves as a technical authority, strategic thought leader, and innovation driver , responsible for shaping HP's integration fabric, API economy, and AI enablement strategy across Digital Tech. The Distinguished Engineer will define long-term architecture vision, influence enterprise-wide technology decisions, and ensure scalable, secure, and AI-ready platforms that accelerate business outcomes. This role operates at the intersection of integration, APIs, data, and AI , driving foundational capabilities that power HP's digital transformation and agentic AI future. Key Responsibilities API & AI-First API Strategy and Governance Define and lead HP's AI-first API strategy , ensuring all enterprise APIs are discoverable, reusable, and optimized for machine and agent consumption Institutionalize the API-as-a-Product operating model, with clear ownership, lifecycle governance, and measurable business value Own and enforce enterprise-wide API governance standards, covering design, lifecycle, security, and AI readiness Define and operationalize the AI-Ready API Framework , including automated governance gates to ensure production readiness Enable HP's Unified API & Agentic AI Strategy , positioning APIs as the foundation for enterprise AI adoption Establish standards for emerging integration paradigms, including event-driven architectures and MCP (Model Context Protocol) Platform AI Enablement & Governance Orchestrate AI enablement and adoption across strategic platforms (SAP, ServiceNow, Adobe, MuleSoft, NOVA) Own the enterprise AI/ML governance process, including AI board reviews, privacy, risk, and cybersecurity compliance Evaluate and guide platform-native AI capabilities to ensure alignment with enterprise architecture and compliance requirements Lead cross-functional AI enablement initiatives to drive consistent adoption and measurable business outcomes Align platform AI initiatives with enterprise prioritization frameworks (e.g., Digital AI Nerve Center) Evaluate AI tooling, vendor solutions, and partner ecosystems for alignment with integration and platform strategy Enable AI-driven SDLC adoption for partner ecosystems (e.g., NOVA vendors), including onboarding, compliance, and knowledge integration Lead/ support key tech initiatives Lead evaluation of new and emerging tech, conduct POC, and lay down path for adoption. Lead the EPS AI initiatives through AI/ML review board and cyber approval process. Partner with Applied AI teams for knowledge sharing of Enterprise AI initiatives Coach and mentor teams in their AI journey Improve reuse, reduce duplication, and strengthen governance via API-as-a-product discipline Enable scalable, enterprise-grade AI products (e.g., IBDF, AIOps) delivering measurable business value Qualifications & Experience 10+ years of experience in enterprise architecture, integration, and platform engineering Proven track record defining and implementing enterprise integration strategies and API ecosystems at scale Deep expertise in integration patterns (event-driven, messaging, APIs, microservices) and cloud-native architectures Experience leading AI/ML enablement, governance, and platform integration in large enterprises Strong understanding of enterprise platforms (SAP, ServiceNow, Adobe, MuleSoft) and their AI capabilities Demonstrated ability to influence executive stakeholders and drive cross-functional alignment Recognized as a thought leader and technical authority , with experience mentoring senior architects and engineers Leadership Expectations Act as a trusted advisor to executive leadership on enterprise architecture and AI strategy Drive innovation by identifying emerging technologies and translating them into enterprise capabilities Mentor and elevate the technical community, fostering architectural excellence across HP Represent HP externally with partners, customers, and industry forums as a leader in integration and AI Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. Typically has 10+ years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. Preferred Certifications Programming Language/s Certification (Java, C++, Python, JavaScript, or similar) Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API) • Automation • C++ (Programming Language) • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) Cross-Org Skills • Effective Communication • Results Orientation • Learning Agility • Digital Fluency • Customer Centricity Impact & Scope Impacts multiple functions and influences long-term strategic direction across multiple disciplines or areas of HP. Complexity Invents, develops and introduces new methods and techniques that impact multiple disciplines and work groups. Pay & Benefits The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave US benefits overview The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Disclaimer This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
