185 jobs found

Job Description Job Description Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you'll be part of a passionate team dedicated to accomplishing hard things, together. Principal ML Platform Engineer Lead the engineering of software that matters - driving AI automation for the world's largest enterprises. This role is based at our h eadquarters in McLean, Virginia. Appian was built on a culture of in-person collaboration, which we believe is a key driver of our mission to be the best. Employees hired for this position are expected to be in the office 5 days a week to foster that culture and ensure we continue to thrive through shared ideas and teamwork. We believe being in the office provides more opportunities to come together and celebrate working with the exceptional people across Appian. About the Team Appian Engineering spans the full depth of our platform: from the foundational layers that power enterprise scale, to the AI capabilities redefining what automation can do. We operate in a highly collaborative, fast-paced environment focused on technical precision, continuous learning, and high code quality. By joining our team, you will solve real-world problems that directly shape how Appian delivers our AI-Powered Process Automation platform to enterprises around the world. The Opportunity As a Principal Software Engineer, you will serve as a technical linchpin for the team, bringing deep expertise in cloud-native architecture and a track record of influencing engineering direction beyond your immediate scope. Equipped with cutting-edge AI tooling, you will drive the design and delivery of high-complexity engineering solutions, set the technical bar for the team, and lead other engineers towards solutions of real complexity to ensure flawless Enterprise-Grade Orchestration. What You'll Do Develop Clean Software: Architect, build, and optimize high-performance software systems while maintaining a strong personal technical presence on the team. Lead Platform Modernization: Spearhead strategic technological changes and champion code refactoring efforts to keep the core Appian codebase cutting-edge, modern, and performant. Engineer with AI: Use AI coding tools fluently as a force multiplier: generating, reviewing, and critically evaluating AI-assisted code to ship faster without compromising quality or correctness. Lead Architecture & Delivery: Drive technical story breakdowns, acceptance criteria, and architectural design across complex, multi-tier application layers - from feature scoping through implementation. Optimize Performance & Scale: Manage product availability, latency, scalability, and efficiency by engineering deep reliability into our core software systems and performing advanced system tuning. Drive Engineering Excellence: Radiate development best practices across the department, perform meticulous code reviews on design and implementation, and build automation frameworks to prevent problem recurrence. Lead & Grow Engineers: Actively coach and mentor engineers at multiple levels, identify and close skill gaps on the team, and take ownership of accelerating the technical growth of those around you. Influence Technical Documentation: Share your expert domain knowledge regularly across the department, building a reputation as a vital resource and publishing high-quality content to Engineering's permanent documentation site. Required Qualifications Education: Minimum of a Bachelor of Science degree in Computer Science or a related technical/analytical discipline. (Equivalent experience is not accepted in lieu of a degree). Experience: 10+ years of relevant software development experience with a BS (or 8+ years of experience paired with a Master of Science in Computer Science or related field). Technical Mastery: Expert coding, scripting, and debugging proficiency in one or more core enterprise programming languages, specifically Java, Python, or Go. Domain Expertise: Deep working knowledge of distributed systems, cloud infrastructure, and the ability to contribute meaningfully at a senior individual contributor level within that space. Cross-Team Influence: Demonstrated ability to drive technical decisions and shape engineering practices beyond a single team or project scope. AI-Augmented Development: Demonstrated experience using AI coding assistants and a strong ability to evaluate, coach others on, and selectively apply AI-generated code in a production engineering context. Production Mastery: Proven experience developing, optimizing, and maintaining a high-volume, mission-critical production service environment. Communication & Alignment: Exceptional ability to communicate highly technical architectures verbally, visually, and in writing to diverse engineering audiences. Preferred Qualifications Cloud Architecture: Strong experience designing microservices, working with containerization (Docker, Kubernetes), and implementing modern CI/CD pipelines. Cloud Platforms: Deep experience developing and operating infrastructure across public cloud ecosystems, specifically AWS, Azure, and/or GCP. We value experience with enterprise platforms such as Salesforce or ServiceNow, as these skills translate well into our Enterprise-Grade Orchestration environment. What We Equip You With High-Impact Autonomy: A leadership environment where you will have real ownership over your team's direction, the latitude to make meaningful decisions, and participation in broader Engineering discussions. New Hire Orientation: A robust onboarding experience designed to integrate you smoothly into our technology, culture, and leadership model so you can show up for your team from day one. Continuous Enablement: Access to premier learning resources and dedicated learning time focused on both your continued technical growth and your evolution as an engineering leader. Sponsored Certifications: Full corporate sponsorship for professional technical certifications to advance your engineering credentials. The base salary range represents a good faith and reasonable estimate of the range at the time of posting. Actual compensation will be dependent on a number of factors including, but not limited to, the candidate's relevant work experience, qualifications, internal peer equity, and market and business conditions that exist when extending an offer. A discretionary bonus may be awarded in recognition of individual and company performance. In addition, Appian provides generous benefits offerings that include a 401(k) plan with company match, flexible time off, paid parental leave, medical, dental, and vision plans, life insurance, disability insurance, wellness programs, flexible spending accounts, health savings account contributions, an employee referral bonus program, and learning and development resources. Certain positions may be eligible for equity awards. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation, commission, bonus, or benefit plans. Base Salary Range $175,000-$325,000 USD Tools and Resources Training and Development: During onboarding, we focus on equipping new hires with the skills and knowledge for success through department-specific training. Continuous learning is a central focus at Appian, with dedicated mentorship and the First-Friend program being widely utilized resources for new hires. Growth Opportunities: Appian provides a diverse array of growth and development opportunities, including our leadership program tailored for new and aspiring managers, a comprehensive library of specialized department training through Appian University, skills based training, and tuition reimbursement for those aiming to advance their education. This commitment ensures that employees have access to a holistic range of development opportunities. Community: We'll immerse you into our community rooted in respect starting on day one. Appian fosters inclusivity through our 8 employee-led affinity groups. These groups help employees build stronger internal and external networks by planning social, educational, and outreach activities to connect with Appianites and larger initiatives throughout the company. Benefits Appian offers a comprehensive benefits package designed to support your health, wellbeing, and financial future. Benefits may include health coverage, Employee Assistance Program (EAP) with free mental health support, life and disability insurance, an Employee Stock Purchase Program (ESPP), a retirement/pension plan, wellness dollars, tuition reimbursement, family-forming benefits and more. Benefits vary by country-please ask your Talent Acquisition contact for details specific to the location you are applying to. About Appian Appian provides AI automation for mission-critical work. We automate complex processes in large enterprises and governments . click apply for full job details

Job Description Job Description Description: About Us: eSimplicity is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that equip federal agencies with solutions to courageously transform today for a better tomorrow. Responsibilities: The Agentic AI & MCP Specialist will architect, develop, and operationalize next-generation agentic systems powered by advanced LLMs and Model Context Protocol (MCP) frameworks. This role focuses on building intelligent, multi-step, tool-using agents that can autonomously reason, plan, and execute complex workflows across a cloud-based analytics ecosystem. The specialist will design and implement agent orchestration frameworks, integrate model-driven decision logic, and build robust, production-grade agent capabilities that safely leverage emerging AI techniques. This position requires a deeply skilled software developer who combines strong engineering fundamentals with hands-on experience creating agentic systems, working with MCP-based integrations, designing LLM-driven tools, and building secure, scalable AI applications. The role provides technical leadership, explores cutting-edge agentic patterns, drives proof-of-concept innovation, and partners with engineering and product teams to translate experimental architectures into real-world impact. Requirements: Required Qualifications: All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation. Bachelor's Degree and 10+ years of software engineering experience Experience designing, developing, and supporting production applications, platforms, or services. Experience developing agentic AI solutions, including planning, tool utilization, workflow orchestration, multi-step reasoning, or autonomous task execution. Experience designing and implementing Model Context Protocol (MCP) integrations, tool interfaces, or model-driven service architectures. Ability to analyze business, customer, or mission requirements and develop scalable AI-driven solutions that align with technical and operational objectives. Experience with large language model (LLM) development practices, including fine-tuning, retrieval-augmented generation (RAG), prompt engineering, and agent interaction patterns. Proficiency in Python and experience working with APIs, microservices, distributed computing environments, and cloud-native architectures. Experience deploying and integrating AI agents or LLM-enabled applications within cloud environments such as Azure, AWS, or Google Cloud Platform (GCP). Knowledge of MLOps and LLMOps practices, including model versioning, automated testing, deployment automation, monitoring, performance evaluation, and governance. Ability to contribute to solution design discussions, provide technical guidance to team members, and communicate AI-related concepts to technical and non-technical audiences. Experience using version control systems and CI/CD practices, including source code management, automated testing, deployment pipelines, and release management for production environments. Desired Qualifications: Experience building multi-agent systems, agent swarms, or coordinated reasoning frameworks. Familiarity with advanced tool-calling strategies, including dynamic tool selection, function-call planning, or graph-structured task planners. Experience with structured LLM evaluation methods, agent benchmarking, or test harnesses for autonomous systems. Knowledge of performance optimization techniques for LLMs and agents, including caching, model distillation, model routing, or accelerated inference. Background integrating agentic components with large-scale data or analytics platforms (e.g., Databricks, Snowflake, Spark). Hands-on experience developing innovative POCs or experimental agentic architectures in fast-paced R&D environments. Familiarity with emerging agentic frameworks such as Strands Agents, LangGraph, CrewAI, etc. Exposure to safety-oriented design patterns for autonomous systems, including guardrails, validation layers, or constrained-action frameworks. Experience designing and building secure, compliance-aware systems that handle sensitive data in accordance with HIPAA and federal security standards, including implementation of encryption, access controls, auditability, and governance for protected health information (PHI) within AI/LLM workflows. Working Environment : eSimplicity supports a remote work environment operating within the Eastern time zone so we can work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by manager. Occasional travel for training and project meetings. It is estimated to be less than 5% per year. Benefits: eSimplicity offers a comprehensive benefits package, including medical, dental, and vision coverage, 401(k) retirement benefits, paid time off, paid holidays, life and disability insurance, and additional wellness and employee support programs. Eligibility may vary based on employment status and applicable plan terms. Reasonable Accommodation: eSimplicity is committed to providing reasonable accommodations to qualified individuals with disabilities during the application and hiring process. Applicants who need assistance or an accommodation should contact Human Resources. Equal Employment Opportunity: eSimplicity is an Equal Opportunity Employer, including disability and protected veteran status. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability, or any othe

Job Description Job Description Company and Vision PlanetArt's vision is to be the leading seller of personalized and make-on-demand products worldwide. We provide consumers with unmatched tools and content and an unparalleled end-to-end customer experience that result in high-quality, meaningful finished products and memorable celebrations of live events. The company's brands include the popular FreePrints and FreePrints Photobooks apps and the industry leading SimplytoImpress card and stationery site, as well as Personal Creations, CafePress and ISeeMe! Visit to learn more about our brands. We have more than 500 team members across multiple offices, primarily in Calabasas CA, San Diego CA, Woodridge IL, Minneapolis, MN and Pleasanton, CA. We also have team members in two company-owned offices in China, as well as in Europe. Job Overview PlanetArt is seeking a Principal Staff Engineer-Web Platform to serve as a senior technical leader within our engineering organization and a key partner to the VP of Engineering. This is a highly hands-on role focused on building, operating, and scaling high-traffic ecommerce web platforms in a fast-moving production environment. Reporting directly to the VP of Engineering, this engineer will play a critical role in architecting, developing, troubleshooting, and maintaining our LAMP-based web applications and AWS infrastructure. The ideal candidate is equally comfortable writing production code, diagnosing complex site reliability issues, managing cloud infrastructure, and leading technical problem-solving during high-severity incidents. This role requires strong operational judgment and the ability to independently own production challenges across application, database, infrastructure, and deployment layers. The engineer will collaborate closely with our China-based development organization, serving as a senior US-based technical lead responsible for cross-team coordination, code quality, architectural guidance, and production stability. This is an ideal opportunity for an experienced engineer who thrives in high-scale ecommerce environments and enjoys combining deep application engineering with modern cloud operations and production ownership. PLEASE NOTE: Candidates much be local to or willing to relocate to the Calabasas area as we operate on a hybrid work model (3 days onsite, 2 remote) What You'll Do Key Responsibilities Full-Stack Platform Engineering: Design, develop, and maintain scalable features and services across our LAMP-based ecommerce platform, with a strong focus on reliability, performance, maintainability, and operational excellence. Production Operations & Incident Response : Act as a senior technical escalation point for complex production incidents, troubleshooting issues across application, infrastructure, networking, database, CDN, and deployment layers. Lead root cause analysis and drive long-term stability improvements. AWS Infrastructure Ownership : Manage and optimize AWS infrastructure, including deployment architecture, scaling strategies, observability, security, disaster recovery, and cost efficiency. Partner closely with DevOps and engineering leadership on operational best practices. High-Scale Performance Optimization : Monitor and improve application, database, and infrastructure performance for high-traffic consumer web applications. Identify bottlenecks and implement scalable solutions to improve uptime, latency, and system resilience. Cross-Functional Technical Leadership: Partner with Product, Design, Operations, and Customer Experience teams to translate business requirements into scalable technical solutions and ensure successful project execution. Global Engineering Collaboration : Work closely with the China-based engineering team to coordinate development efforts, conduct code reviews, align on architectural direction, manage releases, and maintain strong engineering communication across time zones. Code Quality & Engineering Standards : Champion high engineering standards through code reviews, testing strategies, documentation, observability, and operational best practices. Drive continuous improvement in system reliability and development processes. Technical Mentorship & Leadership : Provide technical mentorship and architectural guidance across the engineering organization. Influence technical direction through hands-on leadership, strong execution, and collaborative problem-solving. Requirements What You Should Have Skills, Qualifications, and Requirements Senior-Level Full-Stack Engineering Experience: 5+ years of professional experience building and operating large-scale web applications, including substantial hands-on experience with the LAMP stack (Linux, Apache, MySQL, PHP). Strong AWS & Cloud Operations Expertise : Deep hands-on experience with AWS services and production cloud environments, including EC2, RDS, S3, Lambda, CloudWatch, networking, scaling, monitoring, and infrastructure troubleshooting. Ecommerce & High-Traffic Website Experience : Experience supporting high-volume consumer-facing websites or ecommerce platforms, with a strong understanding of scalability, uptime, performance optimization, and operational reliability. Production Troubleshooting Expertise : Demonstrated ability to diagnose and resolve complex production issues under pressure, including database replication issues, performance degradation, infrastructure failures, deployment issues, and site outages. Distributed Systems & Database Knowledge : Strong understanding of distributed web architectures, database performance tuning, replication strategies, caching, queuing systems, and fault-tolerant system design. Global Team Collaboration: Experience working effectively with offshore or globally distributed engineering teams, with strong communication, coordination, and cross-cultural collaboration skills. Chinese Language Skills: Ability to communicate in Mandarin (spoken or written) is highly desirable to facilitate collaboration with our China-based engineering team. Engineering Best Practices: Strong understanding of software engineering fundamentals including Git workflows, CI/CD pipelines, automated testing, observability, code review practices, and secure development standards. Ownership Mentality: Self-directed engineer with strong operational instincts, excellent judgment, and the ability to independently own critical technical initiatives from design through production support. Technical Leadership: Demonstrated ability to influence engineering direction, mentor developers, and drive technical excellence through hands-on leadership rather than direct people management. What You Can Expect Working Conditions Work is performed in an office environment with low to moderate noise levels. Position requires regular, continuous use of computer. Position requires regular sitting and standing. Position requires regular interaction with team members through the following methods: in-person, phone, Zoom, Slack, or email. May require occasional travel. This is a hybrid position; employees are expected to be in the office three days per week (Monday, Tuesday, and Thursday) with the option of working remotely two days (Wednesday and Friday). Benefits The compensation range for this position is $130,000-$220,000 annual salary. PlanetArt offers a comprehensive benefits package, including: Health, Dental, and Vision Insurance Life Insurance Pet Insurance Mental Health Insurance 401(k) with matching Comprehensive Time Off Program including Paid Time Off, Sick Days, Paid Holidays, and Floating Holidays Employee Product Discounts

Job Description Job Description Job description At , we solve the most complex and critical challenges by moving quickly from analysis to action when it really matters; creating value that has a lasting impact on companies, their people, and the communities they serve. We hold ourselves accountable by providing space for authenticity, growth, and equity for everyone. has embraced a hybrid work model to provide flexibility and support work-life integration. Travel is part of this position, but frequency may vary based on client, team, and individual circumstances. Relocation assistance is not available for this position. About the Role The Principal AI Engineer sits at the intersection of software engineering, data science, platform architecture, and AI governance. You will be the technical owner of how AI/ML engineering is designed, built, governed, and shipped across a portfolio of products serving all of domains. This is a hands-on engineering and technical leadership position. You will move fluidly between writing production code, architecting multi-tenant AI services, building internal developer tooling, leading security and governance design, and mentoring engineering teams. Your success is measured by team-level outcomes - scalable patterns that outlast your direct involvement. What You'll Do AI Productization & Platform Engineering Design and own the firm's AI productization & governance playbook, covering service patterns, security/compliance standards, model evaluation rubrics, and production-readiness criteria. Build and maintain reusable internal tooling, including AI service scaffolding, evaluation and monitoring tooling, and data infrastructure - designed for team adoption without ongoing hand-holding. Establish AI agent governance policies covering agent permissions, code execution controls, access to internal systems, and human-in-the-loop enforcement. Partner with Security, Legal, and Compliance to define SOC2/ISO-aligned AI controls, vendor DPA requirements, and prompt data classification policies. Establish standardized deployment patterns using containerization, infrastructure-as-code, and CI/CD pipeline templates reusable across teams. Developer Experience & Engineering Excellence Champion AI-assisted development practices across the engineering org, including LLM-integrated development workflows, test-driven development patterns, and reusable tooling standards that scale across teams. Codify modern software development standards (CI/CD, DevOps, testing, delivery quality) referenced by multiple teams as a baseline for new or re-platformed products. Mentor engineers and tech leads with observable improvement in delivery consistency, design quality, and production readiness rigor. Cross-Functional Leadership & Stakeholder Influence Serve as the go-to technical authority on AI/ML, platform architecture, and engineering practices - regularly consulted by senior stakeholders at the design and strategy stages. Bridge technical and non-technical stakeholders, translating complex architectural decisions, AI risk topics, and platform tradeoffs into clear, actionable guidance. What You'll Need Required 15+ years in software engineering, data science, or a closely related technical field. Bachelor's degree or higher in Computer Science, Engineering, or a related field. Deep expertise in AI/ML frameworks and the Python ecosystem, with hands-on experience deploying models to public cloud infrastructure. Demonstrated experience designing and operating multi-tenant AI services and LLM integrations in production. Proven track record leading microservices architecture - decomposing monoliths, defining service contracts, and operationalizing CI/CD for distributed systems. Strong hands-on command of containerization (Docker), infrastructure-as-code (Terraform), and modern DevOps practices. Substantive experience with AI/LLM security - including prompt injection, data boundary enforcement, model supply chain risk, and AI-specific threat modeling. Strong problem-solving skills, especially in building governance frameworks, evaluation rubrics, and reusable platform patterns at scale. Excellent written and verbal communication skills in English; ability to translate complex technical topics to diverse audiences, including executive stakeholders. Experience with Agile methodologies and cross-functional product team collaboration. Preferred / Additional Qualifications Experience applying AI/ML in business consulting, advisory, or professional services contexts. Familiarity with AI service interface and gateway design patterns, including emerging AI integration protocols. Contributions to open-source AI/ML projects, publications, or active involvement in technical communities. Advanced certifications in AI, deep learning, cloud architecture, or security (e.g., AWS/GCP/Azure ML, CISSP). Experience defining AI compliance controls for SOC2, ISO 27001, or TISAX frameworks. Demonstrated enthusiasm for developer education - writing internal guides, running workshops, or building internal tooling communities. Proficiency in additional languages is a plus (Go, Typescript) Demonstrated ability and enthusiasm to mentor and uplift junior team members or peers Willingness to work outside of normal business hours, and in particular as unique projects/needs arise. Ability to work full time in an office and remote environment; physically able to sit/stand at a computer and work in front of a computer screen for significant portions of the workday Must become familiar with, and promote and abide by, our Core Values as defined by the and foster an inclusive environment with people at all levels of an organization

Job Description Job Description Staff / Principal Platform Engineer Location: New York City Hybrid Department: AI Platform & Infrastructure Team Reports to: Vangie Shue - Principal Engineering Manager About AppGate AppGate secures and protects an organization's most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution and Cyber Advisory Services. AppGate ZTNA is the only direct-routed Zero Trust solution built for peak performance, superior protection and seamless interoperability. AppGate Cyber Advisory Services harden your security posture and ensure business continuity. AppGate safeguards Fortune 500 enterprises and government agencies worldwide. Learn more at About the Role As we expand our platform, we are standing up a new AI Platform & Infrastructure team: the engine room of AppGate's AI strategy. This team owns the infrastructure layer that every next-generation security capability is built on, from network observability to AI-driven threat detection and the secure operation of emerging Agentic AI systems. We're looking for a Staff or Principal Platform Engineer to build and operate the foundational platform behind AppGate's AI products. You combine deep DevOps and cloud infrastructure expertise with hands-on experience operationalizing AI/ML systems, and you treat observability as a first-class engineering discipline. This is a rare opportunity to join a small, private, high-impact company where your work directly shapes the architecture, reliability and core platform that defines the future of security. You'll own the platform spanning APIs, cloud and self-managed solutions and AI/ML infrastructure, and you'll make it fast, reliable and observable at scale. This is a high-leverage, hands-on role for a senior engineer who sets technical direction and still ships. Key Responsibilities Build the Platform: design, build and operate the cloud infrastructure, services and pipelines that AppGate's AI and cloud products run on. Strong experience with self-managed technologies (kafka, elasticsearch) and Kubernetes are a must. Infrastructure as Code & Deployment Orchestration: Terraform and Helm for cloud provisioning, service deployment and configuration management. Implement Observability: instrument APIs, cloud services and AI/ML infrastructure with metrics, logging, tracing and alerting, and define SLOs and operational health metrics that teams trust. Data Platform: real-time and batch data ingestion pipelines, feature stores and data quality. Integrations: third-party connectors, APIs and platform integrations. Operationalize AI/ML: build model serving and inference pipelines, experiment tracking and the MLOps tooling for deployment, versioning, drift monitoring and lifecycle management. Engineer for reliability & automation: apply SRE practices to reduce toil, improve resilience and keep latency and uptime within target across the platform. Automate everything - deliver infrastructure-as-code, CI/CD and self-service tooling so product teams ship safely and quickly. Set technical direction: define platform standards, architecture and best practices, and raise the engineering bar through design reviews and mentorship. Collaborate cross-functionally: partner with data scientists, product teams and leadership to align platform investment with AppGate's strategic vision. Required Qualifications Experience: extensive platform, infrastructure or SRE engineering experience, with a track record of operating production systems at scale. Staff-level candidates typically bring 8+ years and Principal-level candidates 12+ years, though we hire on demonstrated impact. DevOps depth: strong command of infrastructure-as-code (Terraform or equivalent), CI/CD, containers and orchestration (Docker, Kubernetes), and cloud platforms (AWS). Observability expertise: hands-on experience implementing observability across APIs, cloud services and distributed systems using tools such as Prometheus, Grafana, OpenTelemetry, the ELK stack or comparable, including SLO and error-budget practice. Data platform skills: familiarity with real-time and batch ingestion pipelines, feature stores and data quality at production scale. Engineering craft: fluency in a primary backend language (Python, Go or similar) and a strong bias toward automation, testing and reliable, maintainable systems. Leadership: a record of setting technical direction, leading complex initiatives across teams, mentoring senior engineers, while still being very hands-on. Mindset: pragmatic, rigorous and ownership-driven. You thrive in a small, fast-moving environment and enjoy building foundations others depend on. Preferred Qualifications AI/ML infrastructure: experience building or operating model serving, inference pipelines and MLOps tooling such as MLflow, Kubeflow, SageMaker or equivalent, including model deployment, versioning and drift monitoring. Networking & Zero Trust fundamentals: working knowledge of the network and routing layer beneath modern access solutions - TCP/IP, TLS, tunneling/overlay networks, packet routing and filtering, DNS and firewalling - and familiarity with Zero Trust Network Access (ZTNA) or adjacent domains (VPN, SDP, SASE, software-defined networking). You can reason about traffic paths, latency and throughput end-to-end, and instrument the network as a first-class observability signal. Compensation Staff: 185k-225k base Principal: 215k-270k base We offer performance bonuses and considerable equity. AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate's policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.

Job Description Job Description Overview We're looking for a Senior Principal AI Engineer to provide hands-on technical leadership across complex, production-grade AI systems. This role is for a builder-architect-someone who has repeatedly taken AI systems from idea to production, understands where they fail at scale, and knows how to unblock teams to move faster without sacrificing outcomes. This is not a pure strategy or people-management role. It is a deeply technical builder role with organizational impact. You will define technical direction by writing code, designing systems, and helping the organization stay in builder mode as complexity and scale increase. What You'll Do Architect and build end-to-end AI systems including LLM orchestration, retrieval layers, agentic workflows, and structured reasoning systems Lead the design of multi-agent and tool-calling systems that operate reliably in production Establish and evolve architecture patterns for scalable, cost-aware, and observable AI applications Drive technical decisions across data modeling, AI pipelines, infrastructure, and APIs Define best practices for evaluation, monitoring, and governance of AI systems in production Mentor senior engineers through design reviews, code reviews, and system-level debugging Translate ambiguous business and domain problems into clear technical strategies Stay ahead of emerging AI techniques and integrate what matters-without chasing hype Core Skills & Experience 12+ years of software engineering experience, with deep hands-on experience building AI/ML systems in production Strong proficiency in TypeScript, React, Go, Python and modern AI frameworks Extensive experience with LLMs, including RAG, tool use, prompt systems, and agentic architectures Proven ability to design and ship large-scale AI systems that run reliably in real-world environments Strong architectural judgment across data systems, AI models, infrastructure, and application layers Deep understanding of AI failure modes: hallucination, drift, brittleness, latency, and cost blowups Excellent communication skills-able to explain technical tradeoffs to both technical and non-technical audiences Track record of shipping systems end-to-end, not just prototypes or research work Builder Mentality (This Is Core to the Role) We are explicitly looking for builders. By " builder, " we mean an operating mode, not a title. Builders: Bias toward systems that solve user needs, not perfect abstractions Move comfortably from ambiguity first draft iteration production Optimize for learning velocity and customer impact, not theoretical completeness Are willing to build the entire arc of a system to surface real constraints early Treat quality as something you earn through iteration, not something you gate progress with Understand that the last 10-20% of a system-integration, edge cases, UX, usability, reliability-is where real work happens At the Principal level, being a builder also means: Helping the organization stay in builder mode as it grows Collapsing unnecessary complexity rather than introducing more process Knowing when architectural rigor matters, and when it is premature Pulling promising work across the finish line instead of waiting for "perfect readiness" Modeling speed, ownership, and clarity for other senior engineers Your impact is measured not only by what you build, but by how much faster and more effectively others can build because of you. Preferred Experience (Domain-Flexible Specialties) Knowledge graph architecture, ontology design, or semantic modeling in complex domains Graph databases, graph query languages, or graph ML techniques Hybrid systems combining structured reasoning with LLM-based approaches Entity resolution, schema alignment, or knowledge fusion at scale AI systems requiring explainability, auditability, or lineage tracking Experience building AI systems in regulated or high-stakes domains (finance, healthcare, legal, government) MLOps, evaluation infrastructure, or long-running AI services operating at scale What You'll Love Owning the technical direction of real AI systems that make it into production Solving hard, ambiguous problems where architecture and execution matter equally Leading through hands-on building, not layers of process Working in an environment that values shipping, learning, and iteration over perfection Having the latitude to shape both systems and how teams build them About Us We are an AI-first company, and we mean that literally. AI is not a feature we bolt on. It's not a marketing layer. It's not a roadmap experiment. It is the foundation of how we design, build, and operate. We are building systems where machines do what machines do best: pattern recognition, synthesis, analysis at scale. As well as what humans do what humans do best: judgment, context, trust, and accountability. That means rethinking workflows from the ground up. Not "how do we add AI to this process?" but "how should this process exist in a machine-augmented world?" We care deeply about shipping real systems that work in production. In regulated environments. With real customers. At scale. If you're excited to help invent the next way software is built and deployed, and to do it alongside a team of deeply pragmatic, AI-obsessed builders, we'd love to talk. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. This is a hands-on technical role for a security-minded software developer who understands how applications are designed, written, deployed, and operated. You will partner directly with engineering, platform, architecture, and product teams to translate security requirements into practical guidance, reusable patterns, shared services, and automated controls that help teams deliver products faster and more securely. The ideal candidate combines hands-on software development experience with deep knowledge of application security, AI security, attack vectors, vulnerability remediation, and security automation. What You'll Do: Partner with development teams to incorporate security requirements throughout application design, development, testing, deployment, and operations Conduct security architecture reviews, threat modeling, secure design reviews, and assessments of applications, APIs, cloud services, and AI-enabled systems Write and review code to identify vulnerabilities, attack vectors, and opportunities to strengthen secure development practices Develop reusable security patterns, shared services, and automated guardrails that help engineering teams deliver products securely and efficiently Assess and secure AI, machine learning, generative AI, and large language model solutions, including the secure use of AI-assisted development tools Integrate automated security testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning Design security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments Partner with engineering and cybersecurity teams to assess risk, remediate vulnerabilities, respond to security concerns, and promote a security-first engineering culture Basic Requirements: Degree in Computer Science, Information Security, Engineering, or a related technical field, or equivalent professional experience Typically requires 7 or more years of relevant experience in application security, product security, software development, security engineering, DevSecOps, or a related discipline Hands-on experience writing, reviewing, and deploying application code using TypeScript, Java, Ruby, Python, or comparable languages Strong understanding of application attack vectors, secure coding practices, software vulnerabilities, and modern application architectures Experience conducting threat modeling, security architecture reviews, secure design reviews, and vulnerability remediation Experience implementing DevSecOps practices and integrating automated security controls into CI/CD pipelines Experience securing AI/ML platforms, generative AI solutions, large language model applications, or AI-assisted development workflows Experience with cloud platforms, containers, Kubernetes, infrastructure-as-code, security automation, and application security testing tools Preferred Skills and Experience: Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework Experience creating reusable security services, secure development patterns, engineering guardrails, or policy-as-code solutions Experience with CI/CD and infrastructure technologies such as GitHub Actions, Azure DevOps, GitLab, Jenkins, or Terraform Experience supporting frameworks such as SOC 2, HIPAA, SOX, NIST CSF, or ISO 27001 Ability to translate complex security requirements and technical risks into practical guidance for development teams Strong collaboration and influencing skills, with the ability to advance security without unnecessarily slowing product delivery McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $140,300 - $233,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!

Job DescriptionJob DescriptionJob Title: Artificial Intelligence Senior Associate Location: Dearborn, MI (local preferred) Duration: 12 Months (with potential for extension) Interview: Interview onsite in South Lyon/Novi, MI Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week. Position Description: Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Key Responsibilities: Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation Skills Required: Google Cloud Platform Experience Required: Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). 3+ years building production software systems, including 1-2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production - not just notebooks or demos. As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking . Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask). Hands-on experience with agent orchestration frameworks - LangGraph, CrewAI, LlamaIndex, or equivalent - for building stateful, multi-step, tool-using agent workflows. Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services. Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build). Experience building evaluation and observability pipelines for LLM/agent systems - offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost. Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices. Experience Preferred: Experience with cost optimization and model routing - designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale. Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases. Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data. Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents. Prior experience in a startup or 0-to-1 product environment, comfortable with ambiguity and fast-evolving requirements. Education Required: Bachelor's Degree Education Preferred: Master's Degree Additional Information: Architect and deploy the production multi-agent orchestration layer (interpreter/orchestrator, NL-to-SQL agent, visualization agent, RCA/RAG agent, report composition agent, notification agent), using modern agent frameworks with state management and checkpointing rather than ad-hoc loops. Design and productionize RAG pipelines (chunking, embeddings, hybrid retrieval, reranking) grounded in approved schemas, engineering documentation, and historical issue records. Own BigQuery integration and enforce safe, least-privilege, validated execution of LLM-generated SQL. Build CI/CD, containerization, and infrastructure-as-code for deploying agent services on GCP (Cloud Run/GKE, Vertex AI). Implement evaluation pipelines and observability/tracing for every agent (golden datasets, LLM-as-judge scoring, regression alerts) so quality is measurable, not assumed. Implement guardrails, prompt-injection defenses, and human-in-the-loop approval checkpoints to ensure correctness and safety before any output triggers downstream action. Design cost/latency optimization strategies, including tiered model routing (cheap filter models vs. high-capability deep-dive models) and caching. Integrate validated outputs with operational systems (Salesforce ticketing, driver/site-manager notifications) and report export pipelines (PDF/HTML/spreadsheet). Collaborate with data scientists to productionize prototypes (anomaly detection, diagnostic agents) into scalable, monitored services. Establish versioning, testing, and safe rollout practices (canary/shadow deployments) for evolving agent logic.

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. This is a hands-on technical role for a security-minded software developer who understands how applications are designed, written, deployed, and operated. You will partner directly with engineering, platform, architecture, and product teams to translate security requirements into practical guidance, reusable patterns, shared services, and automated controls that help teams deliver products faster and more securely. The ideal candidate combines hands-on software development experience with deep knowledge of application security, AI security, attack vectors, vulnerability remediation, and security automation. What You'll Do: Partner with development teams to incorporate security requirements throughout application design, development, testing, deployment, and operations Conduct security architecture reviews, threat modeling, secure design reviews, and assessments of applications, APIs, cloud services, and AI-enabled systems Write and review code to identify vulnerabilities, attack vectors, and opportunities to strengthen secure development practices Develop reusable security patterns, shared services, and automated guardrails that help engineering teams deliver products securely and efficiently Assess and secure AI, machine learning, generative AI, and large language model solutions, including the secure use of AI-assisted development tools Integrate automated security testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning Design security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments Partner with engineering and cybersecurity teams to assess risk, remediate vulnerabilities, respond to security concerns, and promote a security-first engineering culture Basic Requirements: Degree in Computer Science, Information Security, Engineering, or a related technical field, or equivalent professional experience Typically requires 7 or more years of relevant experience in application security, product security, software development, security engineering, DevSecOps, or a related discipline Hands-on experience writing, reviewing, and deploying application code using TypeScript, Java, Ruby, Python, or comparable languages Strong understanding of application attack vectors, secure coding practices, software vulnerabilities, and modern application architectures Experience conducting threat modeling, security architecture reviews, secure design reviews, and vulnerability remediation Experience implementing DevSecOps practices and integrating automated security controls into CI/CD pipelines Experience securing AI/ML platforms, generative AI solutions, large language model applications, or AI-assisted development workflows Experience with cloud platforms, containers, Kubernetes, infrastructure-as-code, security automation, and application security testing tools Preferred Skills and Experience: Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework Experience creating reusable security services, secure development patterns, engineering guardrails, or policy-as-code solutions Experience with CI/CD and infrastructure technologies such as GitHub Actions, Azure DevOps, GitLab, Jenkins, or Terraform Experience supporting frameworks such as SOC 2, HIPAA, SOX, NIST CSF, or ISO 27001 Ability to translate complex security requirements and technical risks into practical guidance for development teams Strong collaboration and influencing skills, with the ability to advance security without unnecessarily slowing product delivery McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $140,300 - $233,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. This is a hands-on technical role for a security-minded software developer who understands how applications are designed, written, deployed, and operated. You will partner directly with engineering, platform, architecture, and product teams to translate security requirements into practical guidance, reusable patterns, shared services, and automated controls that help teams deliver products faster and more securely. The ideal candidate combines hands-on software development experience with deep knowledge of application security, AI security, attack vectors, vulnerability remediation, and security automation. What You'll Do: Partner with development teams to incorporate security requirements throughout application design, development, testing, deployment, and operations Conduct security architecture reviews, threat modeling, secure design reviews, and assessments of applications, APIs, cloud services, and AI-enabled systems Write and review code to identify vulnerabilities, attack vectors, and opportunities to strengthen secure development practices Develop reusable security patterns, shared services, and automated guardrails that help engineering teams deliver products securely and efficiently Assess and secure AI, machine learning, generative AI, and large language model solutions, including the secure use of AI-assisted development tools Integrate automated security testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning Design security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments Partner with engineering and cybersecurity teams to assess risk, remediate vulnerabilities, respond to security concerns, and promote a security-first engineering culture Basic Requirements: Degree in Computer Science, Information Security, Engineering, or a related technical field, or equivalent professional experience Typically requires 7 or more years of relevant experience in application security, product security, software development, security engineering, DevSecOps, or a related discipline Hands-on experience writing, reviewing, and deploying application code using TypeScript, Java, Ruby, Python, or comparable languages Strong understanding of application attack vectors, secure coding practices, software vulnerabilities, and modern application architectures Experience conducting threat modeling, security architecture reviews, secure design reviews, and vulnerability remediation Experience implementing DevSecOps practices and integrating automated security controls into CI/CD pipelines Experience securing AI/ML platforms, generative AI solutions, large language model applications, or AI-assisted development workflows Experience with cloud platforms, containers, Kubernetes, infrastructure-as-code, security automation, and application security testing tools Preferred Skills and Experience: Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework Experience creating reusable security services, secure development patterns, engineering guardrails, or policy-as-code solutions Experience with CI/CD and infrastructure technologies such as GitHub Actions, Azure DevOps, GitLab, Jenkins, or Terraform Experience supporting frameworks such as SOC 2, HIPAA, SOX, NIST CSF, or ISO 27001 Ability to translate complex security requirements and technical risks into practical guidance for development teams Strong collaboration and influencing skills, with the ability to advance security without unnecessarily slowing product delivery McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $140,300 - $233,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. This is a hands-on technical role for a security-minded software developer who understands how applications are designed, written, deployed, and operated. You will partner directly with engineering, platform, architecture, and product teams to translate security requirements into practical guidance, reusable patterns, shared services, and automated controls that help teams deliver products faster and more securely. The ideal candidate combines hands-on software development experience with deep knowledge of application security, AI security, attack vectors, vulnerability remediation, and security automation. What You'll Do: Partner with development teams to incorporate security requirements throughout application design, development, testing, deployment, and operations Conduct security architecture reviews, threat modeling, secure design reviews, and assessments of applications, APIs, cloud services, and AI-enabled systems Write and review code to identify vulnerabilities, attack vectors, and opportunities to strengthen secure development practices Develop reusable security patterns, shared services, and automated guardrails that help engineering teams deliver products securely and efficiently Assess and secure AI, machine learning, generative AI, and large language model solutions, including the secure use of AI-assisted development tools Integrate automated security testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning Design security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments Partner with engineering and cybersecurity teams to assess risk, remediate vulnerabilities, respond to security concerns, and promote a security-first engineering culture Basic Requirements: Degree in Computer Science, Information Security, Engineering, or a related technical field, or equivalent professional experience Typically requires 7 or more years of relevant experience in application security, product security, software development, security engineering, DevSecOps, or a related discipline Hands-on experience writing, reviewing, and deploying application code using TypeScript, Java, Ruby, Python, or comparable languages Strong understanding of application attack vectors, secure coding practices, software vulnerabilities, and modern application architectures Experience conducting threat modeling, security architecture reviews, secure design reviews, and vulnerability remediation Experience implementing DevSecOps practices and integrating automated security controls into CI/CD pipelines Experience securing AI/ML platforms, generative AI solutions, large language model applications, or AI-assisted development workflows Experience with cloud platforms, containers, Kubernetes, infrastructure-as-code, security automation, and application security testing tools Preferred Skills and Experience: Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework Experience creating reusable security services, secure development patterns, engineering guardrails, or policy-as-code solutions Experience with CI/CD and infrastructure technologies such as GitHub Actions, Azure DevOps, GitLab, Jenkins, or Terraform Experience supporting frameworks such as SOC 2, HIPAA, SOX, NIST CSF, or ISO 27001 Ability to translate complex security requirements and technical risks into practical guidance for development teams Strong collaboration and influencing skills, with the ability to advance security without unnecessarily slowing product delivery McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $140,300 - $233,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!

Job DescriptionJob DescriptionJob Title: Artificial Intelligence Senior Associate Location: Dearborn, MI (local preferred) Duration: 12 Months (with potential for extension) Interview: Interview onsite in South Lyon/Novi, MI Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week. Position Description: Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Key Responsibilities: Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation Skills Required: Google Cloud Platform Experience Required: Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). 3+ years building production software systems, including 1-2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production - not just notebooks or demos. As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking . Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask). Hands-on experience with agent orchestration frameworks - LangGraph, CrewAI, LlamaIndex, or equivalent - for building stateful, multi-step, tool-using agent workflows. Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services. Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build). Experience building evaluation and observability pipelines for LLM/agent systems - offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost. Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices. Experience Preferred: Experience with cost optimization and model routing - designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale. Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases. Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data. Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents. Prior experience in a startup or 0-to-1 product environment, comfortable with ambiguity and fast-evolving requirements. Education Required: Bachelor's Degree Education Preferred: Master's Degree Additional Information: Architect and deploy the production multi-agent orchestration layer (interpreter/orchestrator, NL-to-SQL agent, visualization agent, RCA/RAG agent, report composition agent, notification agent), using modern agent frameworks with state management and checkpointing rather than ad-hoc loops. Design and productionize RAG pipelines (chunking, embeddings, hybrid retrieval, reranking) grounded in approved schemas, engineering documentation, and historical issue records. Own BigQuery integration and enforce safe, least-privilege, validated execution of LLM-generated SQL. Build CI/CD, containerization, and infrastructure-as-code for deploying agent services on GCP (Cloud Run/GKE, Vertex AI). Implement evaluation pipelines and observability/tracing for every agent (golden datasets, LLM-as-judge scoring, regression alerts) so quality is measurable, not assumed. Implement guardrails, prompt-injection defenses, and human-in-the-loop approval checkpoints to ensure correctness and safety before any output triggers downstream action. Design cost/latency optimization strategies, including tiered model routing (cheap filter models vs. high-capability deep-dive models) and caching. Integrate validated outputs with operational systems (Salesforce ticketing, driver/site-manager notifications) and report export pipelines (PDF/HTML/spreadsheet). Collaborate with data scientists to productionize prototypes (anomaly detection, diagnostic agents) into scalable, monitored services. Establish versioning, testing, and safe rollout practices (canary/shadow deployments) for evolving agent logic.

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. This is a hands-on technical role for a security-minded software developer who understands how applications are designed, written, deployed, and operated. You will partner directly with engineering, platform, architecture, and product teams to translate security requirements into practical guidance, reusable patterns, shared services, and automated controls that help teams deliver products faster and more securely. The ideal candidate combines hands-on software development experience with deep knowledge of application security, AI security, attack vectors, vulnerability remediation, and security automation. What You'll Do: Partner with development teams to incorporate security requirements throughout application design, development, testing, deployment, and operations Conduct security architecture reviews, threat modeling, secure design reviews, and assessments of applications, APIs, cloud services, and AI-enabled systems Write and review code to identify vulnerabilities, attack vectors, and opportunities to strengthen secure development practices Develop reusable security patterns, shared services, and automated guardrails that help engineering teams deliver products securely and efficiently Assess and secure AI, machine learning, generative AI, and large language model solutions, including the secure use of AI-assisted development tools Integrate automated security testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning Design security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments Partner with engineering and cybersecurity teams to assess risk, remediate vulnerabilities, respond to security concerns, and promote a security-first engineering culture Basic Requirements: Degree in Computer Science, Information Security, Engineering, or a related technical field, or equivalent professional experience Typically requires 7 or more years of relevant experience in application security, product security, software development, security engineering, DevSecOps, or a related discipline Hands-on experience writing, reviewing, and deploying application code using TypeScript, Java, Ruby, Python, or comparable languages Strong understanding of application attack vectors, secure coding practices, software vulnerabilities, and modern application architectures Experience conducting threat modeling, security architecture reviews, secure design reviews, and vulnerability remediation Experience implementing DevSecOps practices and integrating automated security controls into CI/CD pipelines Experience securing AI/ML platforms, generative AI solutions, large language model applications, or AI-assisted development workflows Experience with cloud platforms, containers, Kubernetes, infrastructure-as-code, security automation, and application security testing tools Preferred Skills and Experience: Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework Experience creating reusable security services, secure development patterns, engineering guardrails, or policy-as-code solutions Experience with CI/CD and infrastructure technologies such as GitHub Actions, Azure DevOps, GitLab, Jenkins, or Terraform Experience supporting frameworks such as SOC 2, HIPAA, SOX, NIST CSF, or ISO 27001 Ability to translate complex security requirements and technical risks into practical guidance for development teams Strong collaboration and influencing skills, with the ability to advance security without unnecessarily slowing product delivery McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $140,300 - $233,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!

What you will do We are seeking a Manufacturing IT Platform Engineer with 8-10 years of traditional software development hands-on experience using AI-assisted development tools (e.g., Claude.ai, ChatGPT, GitHub Copilot). The role focuses on building productized, reusable capabilities for MoM/MES integration, manufacturing data platforms, and edge deployments, using containers and Kubernetes to deploy and support solutions in manufacturing plants. This role is ideal for an engineer who wants to build real systems used on the shop floor, leverage AI tools to accelerate development, and grow into a strong manufacturing platform contributor. How you will do it Design and develop services supporting MoM/MES use cases such as production events, quality data, and traceability. Build manufacturing data pipelines and APIs for real-time and near real time shop-floor data. Develop and maintain edge-deployed applications that interface with plant systems (MES, SCADA, historians, equipment data). Use AI development tools (Claude.ai, Copilot studio) for: Code generation and refactoring Test creation and debugging Documentation and design acceleration Configuration of the MOM/MES Containerize applications using Docker and deploy using Kubernetes (on prem or edge environments). Support plant deployments, validation, and basic production support. Collaborate with senior engineers and architects to improve reliability, scalability, and usability of the platform. What we look for Required 8-10 years of traditional software development experience in Manufacturing. 2-3 years of active experience using AI tools for software development. Strong coding skills in Python, Java, Node.js, or .NET. Experience building and consuming REST APIs and data services. Hands-on experience with Docker containers. Working knowledge of Kubernetes concepts (pods, deployments, services). Basic understanding of manufacturing or industrial systems (MES, shop-floor data, production systems). Preferred Exposure to MoM/MES, SCADA, Historian, or IoT systems. Experience with event-driven or streaming architectures (e.g., MQTT, pub/sub concepts). Any experience deploying applications to edge or on-prem environments. Familiarity with CI/CD pipelines and DevOps practices. Experience with manufacturing and shop-floor systems. Comfortable combining traditional engineering skills with AI-assisted development. Product-oriented mindset-focused on reusable, scalable solutions. Willingness to support plant users and learn from operational feedback. Curious, hands-on, and ownership driven. Meadowbrook - Lithium Ion Our Meadowbrook, Michigan plant produces lithium-ion batteries and runs a research lab. We began operations in 2010 and now employ more than 110 people and operate six days per week. We're mindful of the profound impact we have on our planet and are proud to operate in a LEED Gold Certified facility. Our employees are actively involved in the community and volunteer for a variety of local organizations. What you get: Medical, dental and vision care coverage and a 401(k) savings plan with company matching - all starting on date of hire Tuition reimbursement, perks, and discounts Parental and caregiver leave programs All the usual benefits such as paid time off, flexible spending, short-and long-term disability, basic life insurance, business travel insurance, and Employee Assistance Program Global market strength and worldwide market share leadership HQ location earns LEED certification for sustainability plus a full-service cafeteria and workout facility Clarios has been recognized as one of 2026's Most Ethical Companies by Ethisphere. This prestigious recognition marks the fourth consecutive year Clarios has received this distinction. Who we are: Clarios is the force behind the world's most recognizable car battery brands, powering vehicles from leading automakers like Ford, General Motors, Toyota, Honda, and Nissan. With 18,000 employees worldwide, we develop, manufacture, and distribute energy storage solutions while recovering, recycling, and reusing up to 99% of battery materials-setting the standard for sustainability in our industry. At Clarios, we're not just making batteries; we're shaping the future of sustainable transportation. Join our mission to innovate, push boundaries, and make a real impact. Discover your potential at Clarios-where your power meets endless possibilities. Veterans/Military Spouses: We value the leadership, adaptability, and technical expertise developed through military service. At Clarios, those capabilities thrive in an environment built on grit, ingenuity, and passion-where you can grow your career while helping to power progress worldwide. All qualified applicants will be considered without regard to protected characteristics. Equal Employment Opportunity: We recognize that people come with a wealth of experience and talent beyond just the technical requirements of a job. If your experience is close to what you see listed here, please apply. Diversity of experience and skills combined with passion is key to challenging the status quo. Therefore, we encourage people from all backgrounds to apply to our positions. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, status as a protected veteran or other protected characteristics protected by law. As a federal contractor, we are committed to not discriminating against any applicant or employee based on these protected statuses. We will also take affirmative action to ensure equal employment opportunities. Please let us know if you require accommodations during the interview process by emailing . We are an Equal Opportunity Employer and value diversity in our teams in terms of work experience, area of expertise, and all characteristics protected by laws in the countries where we operate. For more information on our commitment to sustainability, diversity, and equal opportunity, please read our latest report . We want you to know your rights because EEO is the law. A Note to Job Applicants: please be aware of scams being perpetrated through the Internet and social media platforms. Clarios will never require a job applicant to pay money as part of the application or hiring process. To All Recruitment Agencies: Clarios does not accept unsolicited agency resumes/CVs. Please do not forward resumes/CVs to our careers email addresses, Clarios employees or any other company location. Clarios is not responsible for any fees related to unsolicited resumes/CVs.

Qualcomm seeks a Sr. Engineer, AI Platforms to design, build, and optimize large scale AI platforms that power next generation wireless, 5G, and connected devices. You will architect end to end AI/ML pipelines, integrate models into Qualcomm chipsets and cloud/edge environments, and ensure high performance, reliability, and security. Partner with silicon, software, and product teams to deliver scalable inference services, tools, and SDKs. Responsibilities include model deployment, performance tuning on heterogeneous hardware, MLOps automation, monitoring, and contributing to technical strategy in a fast paced, innovation driven culture. Responsibilities Architect and develop large-scale AI/ML platforms and services for wireless and 5 G applications Design and implement end-to-end AI pipelines from data ingestion to deployment and monitoring Optimize AI workloads for Qualcomm chipsets, heterogeneous compute, and edge/cloud environments Collaborate with silicon, software, and product teams to integrate AI into commercial products Implement MLOps practices including CI/CD, model versioning, and automated deployment Monitor and improve platform performance, reliability, scalability, and security Contribute to technical strategy, platform roadmap, and best practices for AI engineering Create tools, SDKs, and APIs to enable internal teams and external partners Troubleshoot complex production issues across distributed systems and accelerators Document architectures, designs, and operational runbooks Required Skills Python C++Machine learning frameworks (Tensor Flow, Py Torch, ONNX) MLOps and CI/CD for MLKubernetes and containerization Distributed systems and microservices Cloud platforms (AWS, Azure, or GCP) GPU/accelerator optimization Data pipelines and ETLMonitoring, observability, and performance tuning

AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (AI Foundations, LLM Customization and Finetuning) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar). To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver. In this role, you will report to a Senior Staff Engineering Manager. You will: Lead the design, development and deployment of cutting-edge 4D world models and generative systems for ultra-realistic and controllable sensor and semantics generation for simulation use cases at waymo. Architect and implement scalable and robust ML pipelines for training, evaluating, and deploying large-scale generative models into our simulation infrastructure, including techniques like model distillation and quantization. Build and scale production-ready video generation techniques (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments. Apply Vision Language Models (VLMs) to enhance the semantic understanding and controllability of our world simulation products. Partner with world class research teams across Waymo and Alphabet to leverage State-of-The-Art research in 4D world modeling and generative AI into robust, production-ready solutions. Mentor and provide technical guidance to other engineers on the team. You have: MS or PhD in Computer Science, Machine Learning, Robotics, or a related field. 5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record. Proven experience in developing and training large-scale generative models for video generation (e.g., Diffusion models, Flow Matching) or Vision Language Models (VLMs) and their applications. Deep expertise in 3D World Modeling or 3D computer vision. Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting). Strong programming skills in Python and experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow. We prefer: PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes. Experience with autonomous systems, robotics, or autonomous vehicle simulation. Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving. Experience in C++ for production systems. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000-$263,000 USD