24 jobs found

Job Description Job Description Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit . Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: Shield AI is seeking an experienced System Architect to own the architecture of Hivemind Forge - an AI development ecosystem and the segment of Hivemind that enables developers to build, train, tune, evaluate, optimize, and deploy learning-based autonomy solutions. You will join the Systems Engineering, Integration, & Test (SEIT) team in the Hivemind Enterprise organization. This ecosystem combines developer tools, APIs, data infrastructure, simulation, AI/ML workflows, and GenAI-enabled automation to accelerate the delivery of autonomous capabilities using Vision-Language Models (VLMs), Vision-Language-Action (VLA) models, world models, foundation models, and other applied AI technologies. As the responsible architect, you will define the comprehensive architecture for this product area, maintain architectural integrity across development teams, and ensure the ecosystem can operate across enterprise cloud, high-performance computing, and secure or disconnected deployment environments. You will work at the intersection of software architecture, AI/ML, data architecture, systems engineering, developer experience, and Generative AI-enabled engineering to create an ecosystem that dramatically reduces the time required to transform mission needs and data into deployable, intelligent autonomous capabilities. What you'll do: Own and evolve the architecture of the Hivemind Forge AI development ecosystem. Define and maintain architecture products in an integrated model-based systems engineering (MBSE) environment, connecting architectural intent to engineering execution. Establish architectural patterns, interfaces, APIs, SDK concepts, and technical standards across software, AI/ML, data, simulation, and deployment capabilities. Define the data and metadata architecture underpinning the AI development lifecycle, including schemas, relationships, lineage, provenance, versioning, and lifecycle management. Ensure traceable pedigree across datasets, training configurations, model artifacts, evaluations, software versions, and deployed capabilities to support reproducibility and auditability. Architect GenAI-enabled and agentic development workflows that accelerate data curation, autonomy development, experimentation, evaluation, troubleshooting, and deployment while preserving human oversight, security, verification, and traceability. Define architectural patterns for integrating AI coding assistants, agents, foundation models, and natural-language interfaces with Hivemind development tools, APIs, SDKs, data, simulation, and engineering workflows. Define architecture for scalable AI/ML workloads across cloud, high-performance compute (HPC), and on-premises infrastructure, including orchestration, workload scheduling, containerization, storage, and data movement. Ensure the ecosystem can be deployed and operated in classified, air-gapped, disconnected, and other constrained enterprise environments while preserving security, configuration control, and reproducibility. Ensure AI-assisted and agentic development workflows preserve appropriate provenance, traceability, human oversight, verification, security, and reproducibility, particularly when contributing to deployed autonomous capabilities. Guide architecture for workflows spanning data ingestion and curation, synthetic data generation, model training and tuning, evaluation, optimization, validation, and deployment. Review and approve detailed software and data designs, resolve cross-team architectural issues, and maintain architectural integrity through implementation and integration. Partner with software, AI/ML, data, systems, product, and technical leadership teams to reduce the time from mission need to validated, deployable autonomy. Required qualifications: 10+ years of experience in software or software-intensive systems development, design, and/or architecture. Demonstrated experience architecting complex software platforms, developer ecosystems, SDKs, APIs, AI/ML platforms, or distributed systems. Experience developing AI/ML solutions using synthetic and real-world data. Experience in data modeling and data architecture, including metadata, lineage, provenance, versioning, and lifecycle management. Understanding of how data, training configurations, model artifacts, evaluations, software, and deployments must be connected to provide end-to-end traceability, reproducibility, and auditability. Experience applying Generative AI, AI assistants, or agents to software, AI/ML, or engineering development workflows. Practical understanding of technologies such as Kubernetes, Slurm or comparable workload schedulers, containerization, infrastructure as code, and object/data storage platforms such as S3-compatible systems. Strong technical leadership and communication skills, with the ability to guide detailed design and maintain alignment across multiple engineering teams. Preferred qualifications: Experience designing AI-native or agentic workflows, including tool use, orchestration, retrieval, structured outputs, evaluation, and human-in-the-loop controls. Experience with MLOps, distributed training, simulation, synthetic data generation, experiment tracking, or model registries. Direct experience developing, training, tuning, evaluating, applying, or deploying VLMs, VLAs, world models, foundation models, or related modern AI models. Experience designing, deploying, or operating software and AI/ML platforms in classified, air-gapped, disconnected, or restricted-network environments. Experience with hybrid-cloud, multi-cloud, on-premises, or edge deployment architectures. Experience architecting autonomy, robotics, aerospace, unmanned systems, or other Physical AI applications. Experience applying MBSE methods and tools, including SysML and Cameo/MagicDraw. Experience delivering defense, aerospace, safety-relevant, or other high-assurance systems requiring rigorous configuration management, verification, and traceability. Impact; You will establish the architectural foundation that enables Hivemind users to transform mission needs, data, AI models, and software into deployable autonomous capabilities-faster, repeatedly, and with confidence in how each capability was created, evaluated, and validated. San Diego, CA range:$170,000 - $260,000 San Mateo, CA range: $210,000 - Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 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.

Job Description Job Description Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit . Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: Shield AI is seeking an experienced System Architect to own the architecture of Hivemind Forge - an AI development ecosystem and the segment of Hivemind that enables developers to build, train, tune, evaluate, optimize, and deploy learning-based autonomy solutions. You will join the Systems Engineering, Integration, & Test (SEIT) team in the Hivemind Enterprise organization. This ecosystem combines developer tools, APIs, data infrastructure, simulation, AI/ML workflows, and GenAI-enabled automation to accelerate the delivery of autonomous capabilities using Vision-Language Models (VLMs), Vision-Language-Action (VLA) models, world models, foundation models, and other applied AI technologies. As the responsible architect, you will define the comprehensive architecture for this product area, maintain architectural integrity across development teams, and ensure the ecosystem can operate across enterprise cloud, high-performance computing, and secure or disconnected deployment environments. You will work at the intersection of software architecture, AI/ML, data architecture, systems engineering, developer experience, and Generative AI-enabled engineering to create an ecosystem that dramatically reduces the time required to transform mission needs and data into deployable, intelligent autonomous capabilities. What you'll do: Own and evolve the architecture of the Hivemind Forge AI development ecosystem. Define and maintain architecture products in an integrated model-based systems engineering (MBSE) environment, connecting architectural intent to engineering execution. Establish architectural patterns, interfaces, APIs, SDK concepts, and technical standards across software, AI/ML, data, simulation, and deployment capabilities. Define the data and metadata architecture underpinning the AI development lifecycle, including schemas, relationships, lineage, provenance, versioning, and lifecycle management. Ensure traceable pedigree across datasets, training configurations, model artifacts, evaluations, software versions, and deployed capabilities to support reproducibility and auditability. Architect GenAI-enabled and agentic development workflows that accelerate data curation, autonomy development, experimentation, evaluation, troubleshooting, and deployment while preserving human oversight, security, verification, and traceability. Define architectural patterns for integrating AI coding assistants, agents, foundation models, and natural-language interfaces with Hivemind development tools, APIs, SDKs, data, simulation, and engineering workflows. Define architecture for scalable AI/ML workloads across cloud, high-performance compute (HPC), and on-premises infrastructure, including orchestration, workload scheduling, containerization, storage, and data movement. Ensure the ecosystem can be deployed and operated in classified, air-gapped, disconnected, and other constrained enterprise environments while preserving security, configuration control, and reproducibility. Ensure AI-assisted and agentic development workflows preserve appropriate provenance, traceability, human oversight, verification, security, and reproducibility, particularly when contributing to deployed autonomous capabilities. Guide architecture for workflows spanning data ingestion and curation, synthetic data generation, model training and tuning, evaluation, optimization, validation, and deployment. Review and approve detailed software and data designs, resolve cross-team architectural issues, and maintain architectural integrity through implementation and integration. Partner with software, AI/ML, data, systems, product, and technical leadership teams to reduce the time from mission need to validated, deployable autonomy. Required qualifications: 10+ years of experience in software or software-intensive systems development, design, and/or architecture. Demonstrated experience architecting complex software platforms, developer ecosystems, SDKs, APIs, AI/ML platforms, or distributed systems. Experience developing AI/ML solutions using synthetic and real-world data. Experience in data modeling and data architecture, including metadata, lineage, provenance, versioning, and lifecycle management. Understanding of how data, training configurations, model artifacts, evaluations, software, and deployments must be connected to provide end-to-end traceability, reproducibility, and auditability. Experience applying Generative AI, AI assistants, or agents to software, AI/ML, or engineering development workflows. Practical understanding of technologies such as Kubernetes, Slurm or comparable workload schedulers, containerization, infrastructure as code, and object/data storage platforms such as S3-compatible systems. Strong technical leadership and communication skills, with the ability to guide detailed design and maintain alignment across multiple engineering teams. Preferred qualifications: Experience designing AI-native or agentic workflows, including tool use, orchestration, retrieval, structured outputs, evaluation, and human-in-the-loop controls. Experience with MLOps, distributed training, simulation, synthetic data generation, experiment tracking, or model registries. Direct experience developing, training, tuning, evaluating, applying, or deploying VLMs, VLAs, world models, foundation models, or related modern AI models. Experience designing, deploying, or operating software and AI/ML platforms in classified, air-gapped, disconnected, or restricted-network environments. Experience with hybrid-cloud, multi-cloud, on-premises, or edge deployment architectures. Experience architecting autonomy, robotics, aerospace, unmanned systems, or other Physical AI applications. Experience applying MBSE methods and tools, including SysML and Cameo/MagicDraw. Experience delivering defense, aerospace, safety-relevant, or other high-assurance systems requiring rigorous configuration management, verification, and traceability. Impact; You will establish the architectural foundation that enables Hivemind users to transform mission needs, data, AI models, and software into deployable autonomous capabilities-faster, repeatedly, and with confidence in how each capability was created, evaluated, and validated. San Diego, CA range:$170,000 - $260,000 San Mateo, CA range: $210,000 - Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 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.

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated AI Data Solutions Scientist in the Technology organization at USAA, you will work within our innovative Data Science team and collaborate cross-functionally with our architecture, engineering, and product partners to transform our operations and experiences while producing actionable insights to drive our association forward. As a member of our dynamic community of problem-solvers, you will tackle a broad and evolving spectrum of business targets to provide outstanding impacts for our membership through scaled solutions and cloud technologies, leveraging both structured and unstructured data through traditional pillars of operations research such as simulation, optimization, and machine-learning techniques, as well as a heavy emphasis on cutting-edge technologies with generative AI, large/small language models, and advanced agent frameworks. This team is the backbone of the next generation of AI modeling at USAA, and we hope you join us on the frontier! We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, or Phoenix, AZ. Relocation assistance is not available for this position. What you'll do: Gather, interpret, and manipulate structured and unstructured data to enable advanced analytical solutions for the business. Develop scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value. Select the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs. Develop and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) framework. Composes, and assists peers with composing, technical documents for knowledge persistence, risk management, and technical review audiences. Assess business needs to propose/recommend analytical and modeling projects to add business value. Work with business and analytics leaders to prioritize analytics and modeling problems/research efforts. Build and maintain a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are transparent and based on the highest quality data. Translate complex business request(s) into specific analytical questions, executes on the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations. Manage project milestones, risks, and impediments. Escalates potential issues that could limit project success or implementation. Develop best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards. Maintain expertise and awareness of cutting-edge techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. Serve as a mentor to junior data scientists in modeling, analytics, and computer science tasks. Participate in internal communities that drive the maintenance and transformation of data science technologies and culture. Ensure risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in mathematics, Computer Science, Statistics, Science, Engineering, or quantitative field; OR 4 years of relevant education and/or experience; and 6+ years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in mathematics, computer science, statistics, science and engineering, ai, or other similar quantitative discipline and 4+ years of experience in predictive analytics or data analysis. 4+ years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models. 4+ years of experience in Python for performing statical analysis and/or building and scoring AI/ML models Experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency). Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc. Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics and understanding real-world constraints such as latency, cost, and reliability in AI solution designs. Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts across risk stripes, including experience in the documentation and statistical validation of models for risk management. Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc. Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc. Expertise in LLMs and agentic systems development with frameworks such as LangChain/LangGraph, AgentCore, VertexAI, MCP, or others, with proven experience including prompt engineering, tuning and post-training techniques, multi-agent systems, agent optimization and tool use, RAG and context optimization, and observability and monitoring. MLOps Integration experience in facilitating engineering implementation of production scaled AI solutions in partnership with dedicated AI Engineers in cloud environments such as AWS or GCP. Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results. Experience guiding and mentoring junior technical staff in business interactions and model building. What sets you apart: Financial services, insurance, banking, or other highly regulated industry experience. Experience with cloud-native application development and modernization initiatives. US military experience through military service or a military spouse/domestic partner Compensation range: The salary range for this position is: $143,320 - $273,930. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated AI Data Solutions Scientist in the Technology organization at USAA, you will work within our innovative Data Science team and collaborate cross-functionally with our architecture, engineering, and product partners to transform our operations and experiences while producing actionable insights to drive our association forward. As a member of our dynamic community of problem-solvers, you will tackle a broad and evolving spectrum of business targets to provide outstanding impacts for our membership through scaled solutions and cloud technologies, leveraging both structured and unstructured data through traditional pillars of operations research such as simulation, optimization, and machine-learning techniques, as well as a heavy emphasis on cutting-edge technologies with generative AI, large/small language models, and advanced agent frameworks. This team is the backbone of the next generation of AI modeling at USAA, and we hope you join us on the frontier! We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, or Phoenix, AZ. Relocation assistance is not available for this position. What you'll do: Gather, interpret, and manipulate structured and unstructured data to enable advanced analytical solutions for the business. Develop scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value. Select the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs. Develop and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) framework. Composes, and assists peers with composing, technical documents for knowledge persistence, risk management, and technical review audiences. Assess business needs to propose/recommend analytical and modeling projects to add business value. Work with business and analytics leaders to prioritize analytics and modeling problems/research efforts. Build and maintain a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are transparent and based on the highest quality data. Translate complex business request(s) into specific analytical questions, executes on the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations. Manage project milestones, risks, and impediments. Escalates potential issues that could limit project success or implementation. Develop best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards. Maintain expertise and awareness of cutting-edge techniques. Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies. Serve as a mentor to junior data scientists in modeling, analytics, and computer science tasks. Participate in internal communities that drive the maintenance and transformation of data science technologies and culture. Ensure risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree in mathematics, Computer Science, Statistics, Science, Engineering, or quantitative field; OR 4 years of relevant education and/or experience; and 6+ years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in mathematics, computer science, statistics, science and engineering, ai, or other similar quantitative discipline and 4+ years of experience in predictive analytics or data analysis. 4+ years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models. 4+ years of experience in Python for performing statical analysis and/or building and scoring AI/ML models Experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency). Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc. Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics and understanding real-world constraints such as latency, cost, and reliability in AI solution designs. Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts across risk stripes, including experience in the documentation and statistical validation of models for risk management. Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc. Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc. Expertise in LLMs and agentic systems development with frameworks such as LangChain/LangGraph, AgentCore, VertexAI, MCP, or others, with proven experience including prompt engineering, tuning and post-training techniques, multi-agent systems, agent optimization and tool use, RAG and context optimization, and observability and monitoring. MLOps Integration experience in facilitating engineering implementation of production scaled AI solutions in partnership with dedicated AI Engineers in cloud environments such as AWS or GCP. Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results. Experience guiding and mentoring junior technical staff in business interactions and model building. What sets you apart: Financial services, insurance, banking, or other highly regulated industry experience. Experience with cloud-native application development and modernization initiatives. US military experience through military service or a military spouse/domestic partner Compensation range: The salary range for this position is: $143,320 - $273,930. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Vantor seeks a Senior AI/ML Engineer to advance AI capabilities in our Defense & Aerospace portfolio. You will architect, implement, and optimize machine learning and deep learning solutions within the Data Science & AI department. Responsibilities include building secure, scalable ML pipelines, integrating models into mission systems, and collaborating with cross-functional teams to solve complex operational challenges. You'll mentor peers, influence AI strategy, and help foster Vantor's culture of innovation, diversity, and continuous learning while delivering high-impact, production-grade AI services. Responsibilities Design, build, and deploy ML and deep learning models for defense and aerospace applications Collaborate with cross-functional teams to define AI requirements and translate mission needs into technical solutions Develop secure, scalable ML pipelines and MLOps practices for production systems Optimize model performance, reliability, and latency for real-world operational environments Mentor junior engineers and contribute to Vantor's AI best practices and technical standards Document architectures, experiments, and results for stakeholders and compliance needs Required Skills Machine learning algorithms Deep learning (CNNs, RNNs, transformers) Python Tensor Flow or Py Torch MLOps and CI/CD for MLCloud platforms (AWS/Azure/GCP) Data engineering (ETL, pipelines) Model evaluation and optimization Version control (Git) Secure, scalable software design

Elevance Health is seeking a Lead Senior AI Solutions Engineer to architect and deliver scalable AI solutions that transform healthcare experiences and outcomes. In this mission-driven role, you will design, build, and deploy production-grade ML and generative AI systems across claims, care management, and member engagement. You'll partner with clinicians, data scientists, and product teams to translate business problems into robust AI architectures, lead MLOps and cloud implementation, ensure data privacy and compliance, and mentor engineers while promoting best practices in reliability, performance, and ethical AI. Responsibilities Architect, design, and deliver scalable AI and ML solutions for healthcare use cases. Collaborate with clinicians, data scientists, and product teams to translate requirements into technical designs. Lead end-to-end implementation, including data pipelines, model training, deployment, and monitoring. Establish and maintain MLOps practices, CI/CD pipelines, and cloud infrastructure for AI workloads. Ensure security, compliance, and responsible use of data in line with HIPAA and organizational policies. Evaluate and integrate LLM and generative AI technologies into enterprise solutions. Optimize performance, reliability, and cost for production AI services. Mentor and guide engineers, promoting best practices and technical excellence in AI engineering. Required Skills Python Machine learning model development Deep learning frameworks (Tensor Flow or Py Torch) MLOps and CI/CD for MLCloud platforms (AWS, Azure, or GCP) Microservices and APIs Data engineering with SQL and No SQLContainerization and orchestration (Docker, Kubernetes) LLM and generative AI solutions Healthcare data standards and privacy (HIPAA)

This job is with Gilead Sciences Inc., an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description The Senior Director, Applied AI Solutions, leads the applied AI function within the AI Research Center (ARC), part of Gilead's Clinical Data Science (CDS) organization in Drug Development. As CDS's center of excellence for applied AI, this leader is accountable for the technical and product path from a prioritized AI use case defined by CDS functional organizations to a trusted, reusable capability in production - spanning discovery, experimentation, technical validation, first production release, adoption support, and measured value. The ownership model is deliberate. Business ownership of priorities, requirements, funding, process change, and workflow outcomes remains with the CDS and Development functions, including Clinical Data Engineering & Analytics (CDEA) and Statistical Programming. Enterprise platform services, infrastructure, and scaled production operations and support remain with Enterprise IT and Development Systems. This role supplies the AI expertise, solution engineering, and delivery capacity that make both possible, and is measured on how effectively it accelerates outcomes owned by others. The role combines technical depth, product-minded execution, and people leadership. You will define ARC's applied AI engineering practices - model and prompt lifecycle, evaluation, agent design patterns, solution architecture - and influence the enterprise engineering and architecture standards owned by IT, while remaining close enough to the work to make consequential design decisions and to lead multidisciplinary teams building AI systems for internal CDS and Development users. Priority domains for AI enablement may include clinical data review and insights, study design and operations, biomarker and real-world data workflows, safety and risk detection, regulatory evidence generation, and scientific knowledge access. In each of these domains the owning CDS or Development function leads its own workflow and process transformation agenda; this role provides the AI solutions, methods, and technical expertise that enable it. Applied AI Solutions favors reusable capabilities over isolated proofs of concept. The team builds on Gilead's approved data, cloud, security, privacy, and responsible-AI foundations and on the enterprise platform services provided by IT, and partners closely with ARC's Product Management & Experiences (PMx) and AI Acceleration (AIx) functional (scientific and operational) teams, as well as with Development Systems, Enterprise IT, Information Security, Privacy, Legal, Quality, CDEA, Statistical Programming, and business stakeholders. The mandate: turn high-value Clinical Data Science and Development AI problems - as prioritized by their business owners - into trusted, reusable, production-grade AI capabilities that improve how Gilead designs, conducts, analyzes, and learns from clinical development. Key Responsibilities As the Senior Director of Applied AI Solutions, you will: Applied AI engineering roadmap. In partnership with CDS and Development business owners, Enterprise IT, and ARC leadership, translate prioritized AI demand into a multi-year applied AI engineering and delivery plan tied to CDS and Development outcomes. Business owners decide what to pursue and why; you bring the AI expertise that informs those decisions - feasibility, solution options, effort, data readiness, reuse potential, and technical risk - recommend sequencing, and supply the evidence that allows owners and governance forums to decide whether to scale, redesign, or stop an initiative. Anchor on the core, high-value Development AI priorities while also enabling CDS priorities beyond DevAI and IT-funded use cases; for those outside the enterprise-funded portfolio, CDS functional leaders hold business ownership of the roadmap and requirements, and this role builds agents and solutions directly or guides partners to evaluate, select, and integrate the right third-party capabilities. AI solution design and delivery (0 1). Own the design, build, evaluation, and technical validation of AI services, applications, agents, and shared components through first production release. Co-design with Enterprise IT and Development Systems from the outset so that solutions are built for scale, then hand over to IT-owned platform and operations for enterprise scaling and sustained run, remaining the accountable AI technical partner after transition. Establish reference solutions and workflow designs for model gateways, retrieval-augmented generation (RAG), semantic search, knowledge graphs, multimodal AI, tool use, workflow orchestration, human review, and integration with validated enterprise systems. Agentic systems and interoperability. Guide the responsible use of agentic patterns for bounded, auditable CDS workflows. In partnership with Enterprise IT, Information Security, and Privacy, use open interoperability protocols such as MCP and A2A where appropriate to connect AI applications and agents to governed data, tools, and workflows, and ensure authorization, least-privilege access, provenance, action controls, and human escalation are designed in from the start and that agents are registered in the enterprise agent registry. AI engineering excellence. Define and uphold ARC's applied AI engineering practices - data contracts, model and prompt lifecycle management, evaluation harnesses, LLMOps/MLOps, automated testing, and reproducible releases - while adopting and contributing to the enterprise standards owned by IT for software engineering, infrastructure as code, CI/CD, and security. Build for reliability, latency, cost, maintainability, portability, and graceful failure, not demonstrations alone. Evaluation, observability, and responsible AI. Make evaluation a first-class engineering discipline. Establish offline and online evals, gold-standard datasets, task and outcome metrics, trace-based observability, model and data monitoring, adversarial testing, and incident response. Partner with Responsible AI enterprise teams and control functions to implement risk-tiered governance, privacy, security, records, auditability, explainability, and GxP or regulatory controls when applicable. Adoption and value realization. Co-own product discovery and experience design with PMx and support adoption alongside CDS workflow owners. Operate as an expert partner, not a gatekeeper - augmenting their workflows while they retain ownership of priorities, requirements, process change, and outcomes. Working from baselines the business defines, instrument and report the scientific, operational, quality, and user outcomes AI solutions deliver: cycle-time reduction, improved signal detection, decision quality, reuse, reliability, and sustained utilization. Team and technical leadership. Build, lead, and develop a high-performing team spanning applied AI, machine learning, and software and data engineering. Set a high technical bar through technical design reviews, design critiques, coaching, and selective hands-on prototyping. Create clear career paths, succession plans, and an inclusive culture of scientific rigor, learning, accountability, and responsible experimentation. Ecosystem stewardship. Contribute the AI assessment that informs build, buy, and partner decisions taken jointly with business owners and IT; manage strategic AI vendors within that framework; and assess emerging models, frameworks, and protocols through evidence-based benchmarks. Represent Gilead in selected external collaborations while protecting confidential data, intellectual property, and freedom to operate. WHAT SUCCESS LOOKS LIKE A focused CDS and Development AI portfolio with transparent priorities set by business owners, accountable delivery owners, measurable outcomes, and fewer disconnected pilots. Reusable AI capabilities built on the enterprise platform, and integration patterns co-designed with IT that shorten the path from a validated use case to a supported production service. Several high-value CDS and Development workflows operating in production - delivered with ARC and transitioned cleanly to IT-supported operations - with appropriate human oversight, documented controls, reliable performance, and sustained user adoption. . click apply for full job details

This job is with LexisNexis Legal & Professional , an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About Our Team For over 50 years, LexisNexis Reed Technology has partnered with the U.S. Patent and Trademark Office (USPTO) to deliver secure, scalable, and high-quality patent data processing solutions. Our work transforms complex, unstructured patent submissions into standardized, searchable outputs that power examiner workflows and public dissemination. We operate in a highly regulated environment with strict security requirements, large-scale data volumes, and complex business rules. Our focus is on modernizing legacy workflows through automation, AI, and platform transformation to improve efficiency, accuracy, and cost effectiveness. About the Role Principal AI Engineer - Architecture Track We are seeking a hands-on Principal AI Engineer who can design and build production-grade AI solutions while growing into a broader AI Architect role. This position is ideal for an experienced AI developer or technical lead who has strong engineering depth, understands modern AI architecture, and is ready to expand their influence across platforms, products, and delivery teams. The Principal AI Engineer will work closely with product managers, architects, data scientists, software engineers, security teams, and government stakeholders to translate mission and business needs into secure, scalable, and reusable AI capabilities. The role will initially focus on solution design and hands-on implementation, with increasing responsibility for architecture standards, technical strategy, governance, and cross-team alignment. Conditions of Employment: You must be a U.S. citizen to apply for this position. You must successfully pass a background investigation and achieve Public Trust security clearance. Must be located near the Horsham, PA location for a hybrid onsite schedule. Responsibilities AI Solution Design and Development Design, prototype, and implement AI-powered applications, services, agents, and workflows. Translate business, user, and government mission requirements into practical technical solutions. Develop solutions using large language models, retrieval-augmented generation, machine learning, natural language processing, computer vision, or other relevant AI technologies. Build reusable AI components, services, APIs, evaluation frameworks, and reference implementations. Integrate AI capabilities with enterprise platforms, data sources, workflows, and existing applications. Balance rapid experimentation with the engineering discipline required for secure, reliable production systems. Evaluate models, platforms, frameworks, and vendors based on performance, cost, security, scalability, and mission fit. Architecture and Technical Leadership Contribute to solution architectures covering applications, models, data, integrations, infrastructure, security, and operational monitoring. Partner with senior architects to establish AI architecture patterns, guardrails, standards, and reference architectures. Help teams make informed decisions regarding commercial, open-source, and internally developed AI capabilities. Identify opportunities to create shared AI services and reusable capabilities across products, contracts, and government agencies. Participate in architecture reviews and clearly document technical decisions, tradeoffs, assumptions, and risks. Provide technical guidance, code reviews, mentoring, and hands-on support to engineering and data science teams. Grow into ownership of end-to-end AI solution architecture and broader technical strategy. Government and Stakeholder Engagement Support technical discovery sessions, demonstrations, proofs of concept, proposals, RFIs, and RFP responses. Communicate complex AI concepts, limitations, risks, and tradeoffs clearly to both technical and non-technical audiences. Help move successful prototypes into secure, supportable, and scalable production capabilities. Stay informed about evolving government AI policies, standards, acquisition practices, and responsible-AI expectations. Requirement Bachelor's degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience. Significant professional software engineering experience, including experience delivering production applications or platforms. Hands-on experience developing AI, machine-learning, or data-intensive solutions. Proficiency in Python and experience with APIs, cloud services, data pipelines, software development practices, and source control. Experience with modern generative-AI patterns, such as large language models, retrieval-augmented generation, embeddings, vector search, tool use, structured outputs, or AI agents. Understanding of cloud-native architecture, system integration, identity and access management, observability, and secure development practices. Ability to evaluate technical alternatives and explain architecture decisions and tradeoffs. Experience working across product, engineering, data, security, and business teams. Strong written and verbal communication skills. Ability to satisfy applicable government background, suitability, or contractual requirements. Incorporate security, privacy, accessibility, explainability, auditability, and human oversight into solution designs. Establish appropriate evaluation methods for accuracy, relevance, groundedness, bias, safety, and reliability. Design controls for model and prompt versioning, data lineage, access management, logging, monitoring, and traceability. Partner with cybersecurity, legal, privacy, compliance, and governance teams throughout the solution lifecycle. Ensure solutions align with applicable organizational policies, contractual obligations, and government requirements. Design human-in-the-loop controls based on the risk and impact of the decisions supported or performed by AI. Preferred Qualifications Experience delivering technology solutions for U.S. federal, state, or local government customers. Experience working in government contracting, regulated environments, or programs involving sensitive data. Familiarity with government security and compliance frameworks, such as NIST, FedRAMP, FISMA, or agency-specific controls. Experience with one or more major cloud platforms, particularly AWS, Microsoft Azure, or Google Cloud. Experience with AI orchestration frameworks, model gateways, vector databases, evaluation platforms, MLOps, or LLMOps. Understanding of model evaluation, prompt engineering, fine-tuning, data governance, and responsible-AI practices. Experience moving AI proofs of concept into production. Experience supporting technical proposals, RFIs, RFPs, solution demonstrations, or customer workshops. Prior technical leadership, mentoring, or architecture-review experience. Relevant cloud, architecture, security, data, or AI certifications. Work in a Way That Works for You We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. Working flexible hours to help you fit everything in and work when you are the most productive Working for You We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits Health Savings, Health Care, Dependent Care and Commuter Spending Accounts Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice About the Business LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services. U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process . click apply for full job details

Job Description Job Description The Senior Manager, Enterprise AI and Analytics Leader is responsible for defining and executing the enterprise strategy for artificial intelligence, data, analytics and governance. This leader will transform data into a strategic enterprise asset, enabling business growth, operational excellence, innovation, and competitive advantage. The role serves as the leader of the Enterprise AI Center of Excellence (CoE) and is accountable for establishing enterprise-wide capabilities, governance, platforms, standards, and adoption strategies that enable responsible, scalable, and value-driven use of AI, Analytics and data. Working closely with business leaders, technology teams, and executive leadership, this position drives the organization's data and AI agenda by aligning investments to business priorities, accelerating digital transformation, and delivering measurable business outcomes. Key Responsibilities Enterprise Data & AI Strategy Define and Execute the enterprise AI & analytics, data strategy aligned with corporate objectives. Develop a multi-year roadmap that advances business intelligence, predictive analytics, machine learning, generative AI, and data-driven decision making. Identify opportunities to leverage data and AI to improve customer experience, operational efficiency, revenue growth, and innovation. Advise executive leadership on emerging trends, risks, and opportunities related to data and artificial intelligence. Establish success metrics and value realization frameworks for all major initiatives. Artificial Intelligence & AI Center of Excellence Lead the Enterprise AI Center of Excellence. Develop and execute the enterprise AI roadmap and use-case portfolio. Establish AI governance, operating models, and responsible AI principles. Identify and prioritize high-value AI opportunities across all business functions. Oversee deployment and scaling of generative AI, machine learning, intelligent automation, and advanced analytics solutions. Establish standards for AI development, model management, prompt engineering, and AI lifecycle management. Ensure AI initiatives deliver measurable business value and align with strategic priorities. Partner with Data Governance & Management to Establish enterprise data governance policies, standards, and accountability models. Lead master data management, data quality, metadata management, and data stewardship programs. Ensure data is managed as a strategic enterprise asset. Develop enterprise data architecture and information management standards. Partner with business leaders to improve data ownership, accountability, and trust. Analytics & Business Intelligence Lead enterprise reporting, analytics, and business intelligence capabilities. Drive adoption of self-service analytics and data-driven decision making. Establish standards for reporting, dashboards, KPIs, and performance management. Ensure business leaders have timely access to trusted and actionable information. Advance predictive and prescriptive analytics capabilities across the enterprise. AI Governance, Risk & Responsible AI Establish enterprise AI governance frameworks and oversight processes. Ensure compliance with legal, regulatory, privacy, cybersecurity, and ethical requirements. Chair the AI Governance Council and provide executive-level reporting on AI risks and performance. Develop policies for responsible AI usage, model monitoring, explainability, and risk management. Partner with Legal, HR, Risk, Compliance, and Security teams to ensure effective governance. Business Partnership & Value Realization Act as a strategic advisor to business leaders on data and AI opportunities. Facilitate business prioritization of data and AI investments. Build strong partnerships across Manufacturing, Supply Chain, Commercial, Service, Finance, HR, and Corporate Functions. Lead value realization reviews and ensure business outcomes are achieved. Promote a culture of data literacy and AI-enabled innovation. Data & AI Platform Leadership Define standards supporting data, analytics, and AI. Partner with Enterprise Architecture and Infrastructure teams to establish scalable and secure platforms. Drive cloud-based data and AI platform modernization. Ensure integration of AI capabilities into core business applications and business processes. Manage vendor relationships and strategic technology partnerships. Organizational Leadership Build and lead a high-performing team of data, analytics, and AI professionals. Develop enterprise data literacy and AI literacy programs. Foster a culture of innovation, collaboration, accountability, and continuous improvement. Success Measures Business Impact Revenue growth enabled through data and AI Productivity and efficiency improvements Cost reduction initiatives Business process optimization AI Adoption Number of AI solutions deployed AI utilization and adoption rates Realized business value from AI investments Employee AI literacy and engagement Governance & Risk Compliance with data and AI policies Reduction of data and AI-related risk Audit and regulatory outcomes Organizational Effectiveness Team capability development Stakeholder satisfaction Delivery performance Strategic initiative execution Experience 15+ years of experience in IT, software engineering, data platforms, or enterprise architecture. 5+ years leading enterprise AI, Machine Learning, or Data Science initiatives. Experience dealing with Analytics platforms like SAP and Non SAP solutions Experience delivering large-scale cloud and AI transformation programs. Proven success influencing executive stakeholders and driving cross-functional initiatives. Technical Expertise Generative AI, LLMs, Agentic AI, Retrieval-Augmented Generation (RAG) AI frameworks such as Semantic Kernel, LangChain, CrewAI, AutoGen Azure AI Foundry, Azure OpenAI, Azure Machine Learning Cloud platforms (Azure preferred; AWS/GCP a plus) MLOps, LLMOps, CI/CD, DevSecOps Data platforms including Databricks, Fabric and modern data architectures API, microservices, containerization, and Kubernetes Experience in SAP Joule Experience with Analytic platforms like SAP Business Data Cloud, BW, Databricks, Fabric Preferred Qualifications Experience in Manufacturing Industries. Experience implementing Responsible AI frameworks. Demonstrated thought leadership in AI strategy and enterprise transformation. Demonstrated experience in leading and dealing with analytics strategy and execution Total Compensation = Pay range + Benefits Posted salary ranges are made in good faith. Tennant Co. reserves the right to adjust ranges depending on the experience/qualifications of the selected candidate as well as internal and external equity. The salary range reflects both entry into the role and future growth. Total Compensation = Base Salary + Benefits. Benefits = A comprehensive benefits package including multiple medical plan options, 401(k) with a 100% match up to 6%, paid vacation time, 8 paid company holidays and 3 personal holidays dental and vision coverage, wellness rewards, robust family support programs, company paid disability and life insurance, and a full Employee Assistance Program. Defining Our Employee Value Proposition At Tennant Company, we Discover fulfilling work with opportunities for growth and meaningful recognition. Drive the quality and innovation our customers rely on in our products and services. Connect with people who care about each other, our brands and our communities. These are the principles that define how our employees experience Tennant Company, make Tennant a great place to grow your career, and are at the core of our legacy and future. Together, they serve as guideposts for working with our customers, our partners and one another. Begin your journey with us. Let's reinvent how the world cleans. Equal Opportunity Employer Tennant Company is an equal opportunity employer. Employment decisions are made on the basis of individual skill, ability, reliability, productivity, and other factors important to performance. We do not discriminate on the basis of race, color, creed, religion, sex, national origin, physical or mental disability, age, veteran status, pregnancy, sexual orientation, genetic information, gender identity, or any other basis protected by state or federal law or local ordinance.

Job Description Job Description Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit . Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: The Head of Product Design will define and lead the user experience vision for Hivemind, Shield AI's autonomy development platform. This role is responsible for transforming complex autonomy, robotics, AI, and developer workflows into intuitive experiences that enable engineers, operators, and organizations to develop and deploy resilient autonomy at scale. A major focus of this role will be shaping the next generation of AI-native and agent-driven workflows across the autonomy lifecycle. As Hivemind evolves from traditional software tooling toward AI-assisted autonomy development, simulation, evaluation, deployment, and operations, this leader will help invent entirely new ways for users to collaborate with AI systems, agents, and foundation-model-powered tools. The ideal candidate has deep experience designing AI products, developer platforms, or complex technical systems and can translate emerging AI capabilities into workflows that dramatically improve user productivity and outcomes. This is a highly hands-on role as this leader will manage a team of elite designers. During the first 6-12 months, most of the time will be spent conducting user research, designing experiences, prototyping concepts, facilitating product discovery, and partnering directly with Product and Engineering teams to define the future of autonomy development. What you'll do:User Research & Product Discovery Lead customer research efforts across product development, customer engagement, and solutions teams to identify pain points, workflows, unmet needs, and product opportunities. Establish scalable mechanisms for gathering, synthesizing, and communicating user insights throughout the product development lifecycle. Translate customer and operational feedback into actionable product recommendations, requirements, and design initiatives. Product Design & User Experience Design end-to-end workflows across autonomy development, simulation, testing, analysis, deployment, and operations. Create intuitive experiences for highly technical users including autonomy engineers, software developers, operators, and mission planners. Simplify complex system architectures, data flows, infrastructure tooling, and AI workflows into understandable user experiences. Own the end-to-end experience of the product including training, documentation, tutorials, and overall workflows - help our users get the most of the product. Strategic Product Leadership Partner closely with Product Managers to shape product vision, roadmap priorities, and go-to-market strategies. Drive alignment across Product, Engineering, Design, and Executive Leadership through compelling narratives, prototypes, and visual storytelling. Advocate for user-centered decision making in a highly technical and engineering-driven environment. Design Practice, Systems & Organizational Scale Establish and evolve design standards, design systems, UX principles, and product design best practices across Shield AI. Raise the quality bar for product design, usability, consistency, and customer experience. Grow the product design function by mentoring a small team of designers, shaping design culture, and staying actively involved in critical design work. Champion design wins and impact across the organization, highlighting the important role design plays in delivering successful products. AI-Native Product Design & Agentic Workflows Define the future user experience for AI-assisted autonomy development, simulation, testing, deployment, and operational workflows. Design human-AI collaboration models that enable users to effectively leverage AI agents, copilots, and foundation-model-powered systems. Partner with Product, AI Research, and Engineering teams to create new interaction patterns for agent orchestration, autonomy generation, scenario creation, test generation, and mission planning. Develop frameworks for trust, transparency, explainability, and human oversight within AI-assisted workflows. Help establish industry-leading design patterns for Physical AI development platforms and agent-driven software systems. Required qualifications: 10+ years of experience in Product Design, UX Design, Human Factors, or related fields. Proven track record designing and shipping complex technical products, developer tools, platforms, infrastructure software, data-dense applications, or enterprise systems. Deep technical fluency and ability to effectively collaborate with senior engineering leaders on architecture, technical constraints, and software development workflows. Strong experience conducting user research and translating insights into product strategy and design solutions. Proven ability to influence product direction and organizational decisions without direct authority. Strong understanding of AI-powered product experiences, including conversational interfaces, human-in-the-loop workflows, AI-assisted decision making, and agent-based systems. Experience defining new user experiences in ambiguous technology spaces where industry standards and workflows are still emerging. Experience building and retaining high-performing design teams. Strong portfolio showcasing both strategic thinking and hands-on design execution. Preferred qualifications: Background designing developer platforms, SDKs, cloud infrastructure products, DevOps tooling, or engineering productivity tools. Direct work on AI/ML platforms, MLOps workflows, foundation-model-enabled products, copilots, or agentic systems. Familiarity with autonomy, robotics, simulation, digital twins, mission systems, physical AI, or related development workflows including testing, evaluation, deployment, and operations. Portfolio examples involving command-and-control systems, mission-planning interfaces, operational dashboards, or real-time decision-support tools. Ability to design across integrated hardware/software systems. Domain exposure to defense technology, aerospace, robotics, or other regulated, mission-critical, or high-consequence operational environments. San Diego, CA and Washington, D.C. pay range: $230,000 - $350,000 San Mateo, CA pay range: $280,000 - $420,000 Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 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.

Job Description Job Description Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit . Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: The Head of Product Design will define and lead the user experience vision for Hivemind, Shield AI's autonomy development platform. This role is responsible for transforming complex autonomy, robotics, AI, and developer workflows into intuitive experiences that enable engineers, operators, and organizations to develop and deploy resilient autonomy at scale. A major focus of this role will be shaping the next generation of AI-native and agent-driven workflows across the autonomy lifecycle. As Hivemind evolves from traditional software tooling toward AI-assisted autonomy development, simulation, evaluation, deployment, and operations, this leader will help invent entirely new ways for users to collaborate with AI systems, agents, and foundation-model-powered tools. The ideal candidate has deep experience designing AI products, developer platforms, or complex technical systems and can translate emerging AI capabilities into workflows that dramatically improve user productivity and outcomes. This is a highly hands-on role as this leader will manage a team of elite designers. During the first 6-12 months, most of the time will be spent conducting user research, designing experiences, prototyping concepts, facilitating product discovery, and partnering directly with Product and Engineering teams to define the future of autonomy development. What you'll do:User Research & Product Discovery Lead customer research efforts across product development, customer engagement, and solutions teams to identify pain points, workflows, unmet needs, and product opportunities. Establish scalable mechanisms for gathering, synthesizing, and communicating user insights throughout the product development lifecycle. Translate customer and operational feedback into actionable product recommendations, requirements, and design initiatives. Product Design & User Experience Design end-to-end workflows across autonomy development, simulation, testing, analysis, deployment, and operations. Create intuitive experiences for highly technical users including autonomy engineers, software developers, operators, and mission planners. Simplify complex system architectures, data flows, infrastructure tooling, and AI workflows into understandable user experiences. Own the end-to-end experience of the product including training, documentation, tutorials, and overall workflows - help our users get the most of the product. Strategic Product Leadership Partner closely with Product Managers to shape product vision, roadmap priorities, and go-to-market strategies. Drive alignment across Product, Engineering, Design, and Executive Leadership through compelling narratives, prototypes, and visual storytelling. Advocate for user-centered decision making in a highly technical and engineering-driven environment. Design Practice, Systems & Organizational Scale Establish and evolve design standards, design systems, UX principles, and product design best practices across Shield AI. Raise the quality bar for product design, usability, consistency, and customer experience. Grow the product design function by mentoring a small team of designers, shaping design culture, and staying actively involved in critical design work. Champion design wins and impact across the organization, highlighting the important role design plays in delivering successful products. AI-Native Product Design & Agentic Workflows Define the future user experience for AI-assisted autonomy development, simulation, testing, deployment, and operational workflows. Design human-AI collaboration models that enable users to effectively leverage AI agents, copilots, and foundation-model-powered systems. Partner with Product, AI Research, and Engineering teams to create new interaction patterns for agent orchestration, autonomy generation, scenario creation, test generation, and mission planning. Develop frameworks for trust, transparency, explainability, and human oversight within AI-assisted workflows. Help establish industry-leading design patterns for Physical AI development platforms and agent-driven software systems. Required qualifications: 10+ years of experience in Product Design, UX Design, Human Factors, or related fields. Proven track record designing and shipping complex technical products, developer tools, platforms, infrastructure software, data-dense applications, or enterprise systems. Deep technical fluency and ability to effectively collaborate with senior engineering leaders on architecture, technical constraints, and software development workflows. Strong experience conducting user research and translating insights into product strategy and design solutions. Proven ability to influence product direction and organizational decisions without direct authority. Strong understanding of AI-powered product experiences, including conversational interfaces, human-in-the-loop workflows, AI-assisted decision making, and agent-based systems. Experience defining new user experiences in ambiguous technology spaces where industry standards and workflows are still emerging. Experience building and retaining high-performing design teams. Strong portfolio showcasing both strategic thinking and hands-on design execution. Preferred qualifications: Background designing developer platforms, SDKs, cloud infrastructure products, DevOps tooling, or engineering productivity tools. Direct work on AI/ML platforms, MLOps workflows, foundation-model-enabled products, copilots, or agentic systems. Familiarity with autonomy, robotics, simulation, digital twins, mission systems, physical AI, or related development workflows including testing, evaluation, deployment, and operations. Portfolio examples involving command-and-control systems, mission-planning interfaces, operational dashboards, or real-time decision-support tools. Ability to design across integrated hardware/software systems. Domain exposure to defense technology, aerospace, robotics, or other regulated, mission-critical, or high-consequence operational environments. San Diego, CA and Washington, D.C. pay range: $230,000 - $350,000 San Mateo, CA pay range: $280,000 - $420,000 Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 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.

Job Description Job Description Company Description Vuori is re-defining what athletic apparel looks like: built to move and sweat in but designed with a casual aesthetic to transition into everyday life. We draw inspiration from an active coastal California lifestyle; an integration of fitness, creative expression and life. Our high energy fast paced retail environment is reflected in the clothes we make. We aim to inspire others to take on all aspects of their lives with clarity, enthusiasm and purpose while having a lot of fun along the way. We are proud to be an outlet for opportunity and for personal growth and success. Job Description As Principal, AI Architect and Governance, you will serve as Vuori's senior technical authority for AI platform design, enterprise architecture standards, and responsible AI. You will define how AI systems are designed, built, integrated, and governed across the organization, ensuring they are secure, compliant, scalable, reliable, and aligned with business priorities. This is a senior role for someone who combines deep, hands-on technical expertise with enterprise influence. You will work directly with engineers on architecture and design decisions, translate emerging AI capabilities into pragmatic enterprise patterns, and advise technology, business, security, legal, and data leaders on platform choices and risk. You will raise the quality and consistency of AI development through clear standards, reusable patterns, design reviews, and governance guardrails, without direct people-management responsibility. What you'll get to do: Set direction and raise the bar Shape the evolution of Vuori's enterprise AI architecture, ensuring it keeps pace with the growth of the business and the maturity of the AI ecosystem. Establish reference architectures, engineering standards, and integration patterns that teams across Vuori use when building AI systems. Lead technical evaluations of AI platforms, foundation models, cloud services, and tooling - recommending adoption decisions based on rigorous analysis of performance, cost, security, and fit. Raise the architectural capability of engineers across Vuori through design reviews, pairing, documentation, and reusable patterns others adopt because they are good. Bring clarity to complex, ambiguous problems - including calling out when a proposed AI approach is not the right solution. Make build-versus-buy-versus-partner recommendations that shape the AI platform for years and communicate the rationale clearly to technical and non-technical audiences. Build and maintain AI governance Develop and operationalize Vuori's AI governance framework, covering model risk management, data privacy, bias detection, audit trails, and regulatory compliance. Establish AI engineering standards, security guardrails, testing and evaluation protocols, and responsible AI policies that apply consistently across all teams building AI systems. Create governance structures that give teams a clear path to building and shipping AI responsibly - balancing speed of innovation with enterprise-grade risk management. Partner with Legal, Compliance, Security, and Data teams to ensure AI systems meet applicable regulations, data handling requirements, and ethical standards. Implement ongoing monitoring, incident response, and continuous improvement processes for AI systems in production. Partner across the organization Work closely with senior technology and business leaders to align AI architecture and governance with organizational priorities and investment decisions. Serve as a clear, credible voice on AI architecture and risk in conversations with executive sponsors, engineering leadership, and external partners or auditors. Collaborate with AI product, engineering, and data teams to ensure architectural and governance requirements are understood and built in from the start - not added after the fact. Mentor engineers and technical leads through architectural guidance, design reviews, and the development of shared standards they can apply independently. Measure and evolve Track and report on platform reliability, governance adherence, security posture, and the business impact of AI architecture investments. Continuously assess the AI landscape and incorporate emerging technologies, best practices, and industry standards to keep Vuori's AI ecosystem well-positioned. Use data and operational experience to refine standards, improve governance processes, and remove friction for teams building AI responsibly. Qualifications Who you are: Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field; advanced degree preferred. 12+ years of experience in software engineering, platform engineering, or technology architecture, including significant experience owning enterprise AI or data platform architecture at scale. Demonstrated experience designing and governing AI systems in production - including LLMs, agentic systems, ML pipelines, and model serving infrastructure. Deep expertise in enterprise AI governance, risk management, security, and compliance frameworks. Proven ability to define technical standards, make architecture decisions, and drive adoption across large, cross-functional engineering organizations through influence rather than direct authority. Experience with cloud-native architectures on Azure, AWS, or Google Cloud, and modern AI infrastructure patterns including RAG, vector databases, and orchestration frameworks. Experience building and deploying with frontier AI lab models, platforms, and/or frameworks (i.e. Anthropic, OpenAI, Google, Meta, etc.). Exceptional communication skills, with the ability to explain complex AI architecture and governance requirements clearly to engineering, business, and executive audiences. Strong executive presence and a demonstrated ability to build alignment, challenge assumptions constructively, and influence decisions across a matrixed organization. Preferred Qualifications Experience with enterprise AI governance platforms, model risk management frameworks, or AI regulatory standards such as the EU AI Act or NIST AI RMF. Familiarity with MLOps, model lifecycle management, AI observability, and responsible AI tooling. Experience with low-code and pro-code enterprise AI platforms such as Azure AI Foundry, Microsoft Copilot Studio, or Google Gemini Enterprise. Background in retail, direct-to-consumer, e-commerce, or a similar consumer operating environment. Demonstrated ability to establish and scale practical architecture standards and governance capabilities in high-growth organizations. Active engagement with the broader AI and technology community through publications, speaking, or open-source contributions. Additional Information Our investment in you: At Vuori, we're proud to offer the following to our employees: Health Insurance Savings and Retirement Plan Employee Assistance Program Generous Vuori Discount & Industry Perks Paid Time Off Wellness & Fitness benefits The salary range for this role is $197,500 per year - $264,390 per year. This role is bonus eligible. Vuori is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. All your information will be kept confidential according to EEO guidelines.

Job Description Job Description Position Title: Principal AI Engineer Location: Irvine, California or Anywhere in USA (preferably West Coast based or willing to work in PST Zone) Salary- K-145K/Y Principal AI Engineer to lead the architecture, strategy, and technical evolution of enterprise scale AI platforms and GenAI powered product experiences. Key Responsibilities Define and own enterprise AI platform architecture Lead development of RAG pipelines and AI orchestration frameworks Build production grade AI systems and proofs of concept Establish AI quality, evaluation, and governance standards Drive AI platform design decisions and reusable tooling Required Technical Skills Python engineering expertise LLM applications, vector databases, retrieval infrastructure LangChain, LlamaIndex, semantic search systems AI evaluations, model lifecycle management, observability Scalable GenAI systems and MLOps Required Leadership Skills 12+ years of software engineering experience, with significant tenure at Staff/Principal level. Drive cross team technical decisions, platform direction, and multi team initiatives (architecture alignment, trade off resolution, execution). Define and scale AI driven SDLC standards, including tools, guardrails, and automation patterns. Hands on experience with AI assisted development (e.g., Copilot, Claude Code, Cursor) to deliver production systems; able to articulate workflow impact and guardrails. Strong experience designing and evolving large scale distributed systems (APIs, data pipelines, event driven systems, high scale platforms). Proven cross org leadershipa €driving architecture, standards, and platform initiatives across multiple teams. Elevate engineering quality through code reviews, architecture reviews, and mentoring senior engineers. Strong engineering fundamentals in code quality, testing, CI/CD, and observability while maintaining delivery velocity. Effective communicator with the ability to influence stakeholders and drive alignment without formal authority. Experience collaborating across product, data, security, and infrastructure teams. Track record of documenting and scaling architectural decisions and organizational learnings.

Job Description Job Description Principal Machine Learning Engineer to serve as a hands-on technical leader for machine learning, predictive modeling, scoring, decisioning, and applied AI initiatives. This role will primarily focus on building, validating, deploying, and improving machine learning models , while also bringing principal-level judgment to problem definition, model design, stakeholder engagement, and production readiness. Hands-On Model Development Build, test, validate, and improve machine learning models for scoring, prediction, prioritization, risk detection, engagement, intervention targeting, and decision support. Perform exploratory data analysis, data quality assessment, feature engineering, model training, model selection, and performance evaluation. Develop practical ML models that balance predictive performance, explainability, stability, maintainability, and business usefulness. Work with structured, semi-structured, and operational data to create model-ready datasets and reusable features. Use tools such as Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, or similar platforms and libraries. Move quickly from data exploration to prototype to validated model to production-ready capability. Required Qualifications Professional experience in machine learning, data science, software engineering, analytics engineering, applied AI, or related technical fields. 5 years of hands-on machine learning model development experience, including feature engineering, model training, validation, evaluation, and iteration. 3 years of experience deploying, operationalizing, or supporting models in production or business-critical environments. Strong hands-on experience with Python and SQL. Experience with modern ML and data platforms such as Databricks, Spark, MLflow, Snowflake, Azure, AWS, or similar technologies. Strong understanding of model evaluation, calibration, thresholding, score interpretation, monitoring, drift, retraining, and production ML lifecycle management. Experience translating ambiguous business problems into concrete ML designs, model requirements, validation plans, and measurable outcomes. Ability to explain model behavior, model performance, assumptions, limitations, and tradeoffs to both technical and non-technical stakeholders. Strong engineering discipline, including clean code, reproducibility, versioning, testing, documentation, and maintainability. Ability to work independently as a senior hands-on contributor while also providing technical leadership and modeling judgment. Scoring, Scorecards, and Transparent Models Production ML and MLOps Product and Rapid-Build Execution Generative AI and AI Automation Requirement Shaping and Stakeholder Partnership

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. About the Team Our AI Enablement team drives enterprise-wide adoption of generative AI, spanning platform engineering, governance, and hands-on delivery of AI-powered products and internal tooling. The team builds and operates the infrastructure, integrations, and knowledge systems that let engineering and business teams safely adopt large language models at scale. The Lead AI Engineer joins as the senior technical authority on this team, setting the architectural direction that Senior and Associate AI Engineers build against. Position Summary The Lead AI Engineer provides technical leadership and architecture ownership for the company's AI platform and its embedded delivery initiatives, operating one level above the Senior AI Engineer role. This person owns the technical design of agentic and LLM-powered systems built on large language model APIs, including retrieval-augmented generation (RAG), tool/connector integration, and evaluation/governance tooling, in a highly regulated healthcare environment. The Lead AI Engineer sets architectural standards across AI-embedded product delivery, mentors Senior and Associate AI Engineers, and represents AI platform architecture to engineering leadership and Legal/Compliance/Privacy. Success is measured by the reliability, security, and scalability of the AI systems shipped, the rate at which Senior/Associate engineers adopt the architectural standards this role sets, and this role's influence on AI platform decisions across the organization. Key Responsibilities AI Architecture Leadership: Define the technical architecture and roadmap for LLM/agentic systems - model routing across cloud AI platforms, connector/integration patterns, RAG pipelines, and prompt/evaluation frameworks. Solution Design & Governance: Lead architecture reviews for new AI capabilities and ensure designs meet enterprise security, privacy, and data-provenance requirements. Platform Ownership: Drive the technical design of shared AI platform capabilities, including knowledge-retrieval systems, citation/traceability of AI-generated outputs, and permission-aware access to data. Hands-On Delivery: Personally architect and build high-complexity components on priority AI delivery initiatives where a working system, not just a design doc, is the deliverable. Technical Mentorship: Set coding, architecture, and evaluation standards for Senior and Associate AI Engineers; run design reviews and pair on complex agentic workflows. LLMOps & Responsible AI: Establish secure, observable, and cost-attributed AI operations - usage/spend attribution, abuse monitoring, model evaluation, and rollback strategy - for production LLM systems. Cross-Functional Architecture: Partner with engineering managers, product, platform, and Legal/Compliance to align AI architecture decisions with delivery timelines and enterprise standards. Vendor & Model Strategy: Evaluate foundation model providers and AI tooling vendors; make build-vs-buy and model-selection recommendations. Compliance & Risk: Ensure AI systems handling protected health information (PHI) meet regulatory and enterprise governance requirements. Organizational Impact: Represent AI architecture in cross-company forums and influence enterprise-wide AI platform direction. Priority will be given to candidates who reside in the Columbus, OH metropolitan area. We are unable to provide sponsorship for this role, presently or in the future. Minimum Requirements Bachelor's degree or equivalent experience; typically 8+ years of software engineering experience, including 3+ years focused on AI/ML, LLM, or NLP systems in production. Fewer years required with a relevant Master's or Doctorate. Critical Skills One level of demonstrated technical leadership above a Senior AI Engineer - e.g., owning architecture for a team or platform area, not just a single feature. Deep, hands-on expertise building production LLM applications: prompt engineering, RAG/GraphRAG, agentic workflows, tool use, and evaluation harnesses. Experience with commercial large language model APIs (e.g., Anthropic, OpenAI) and tool-integration protocols such as Model Context Protocol (MCP). Strong software engineering fundamentals: Python and/or Java, REST APIs, event-driven architecture, microservices, and cloud-native design (Azure preferred; AWS/GCP acceptable). Experience with vector/graph retrieval systems, embeddings, and knowledge-base architectures at production scale. Working knowledge of LLMOps/MLOps: usage attribution, cost/spend monitoring, abuse detection, and model evaluation pipelines. Ability to set architectural standards and mentor other engineers through design review and pairing, not just documentation. Familiarity with regulated/healthcare data environments and AI governance frameworks (model risk review, connector approval tiers, PHI handling) is a plus. Preferred Qualifications Advanced degree (M.S. or higher) in Computer Science, AI/ML, or a related technical field. Prior experience leading AI/ML platform or applied-AI teams inside healthcare IT or another highly regulated industry. Experience modernizing legacy systems toward AI-embedded workflows (agent-assisted development, AI-powered risk scoring, AI-driven automation). Experience with Confluence/Jira-based engineering governance and enterprise architecture review boards. Additional Skills Strong awareness of the fast-moving GenAI/agentic landscape and a demonstrated habit of continuous learning. Experience managing relationships with AI tooling vendors and model providers. Clear written and verbal communication for both technical and executive audiences 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 $155,300 - $258,800 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 Description Job Description Description: AI/ML Technical Lead CASCOM ESD Enterprise Analytics/AI Program Schedule: Full-Time / 1.0 FTE Work Arrangement: Primarily Remote with Required Travel to Fort Lee, VA Clearance: Active Final Secret Required The Opportunity We're looking for an AI/ML Technical Lead who still builds. This position requires hands-on technical leadership across AI/ML solutions using CASCOM, GCSS-Army, SAP, and other Army data. The successful candidate must be capable of personally coding, evaluating, deploying, and sustaining models-not simply directing an AI strategy or managing data science teams. Potential use cases include GenAI/OpenAI, RAG, Copilot, document extraction, anomaly detection, equipment-readiness and maintenance forecasting, fleet automation, recommendation capabilities, and supply forecasting. What You'll Do Lead selection and technical refinement of three baseline AI/ML use cases. Define mission questions, data requirements, technical baselines, performance metrics, and acceptance criteria. Perform hands-on data exploration and feature engineering. Develop, train, validate, and comparatively evaluate machine-learning models. Conduct error analysis and document model limitations. Develop selected GenAI, RAG, forecasting, anomaly-detection, or recommendation capabilities. Work with GCSS-Army SMEs to validate business rules and interpret model results. Partner with Azure Data/MLOps engineering resources to package, deploy, version, monitor, and sustain models. Establish appropriate human-review processes for model outputs affecting operational decisions. Develop model cards, evaluation results, release documentation, known limitations, and retraining criteria. Integrate analytical outputs into dashboards, Power Apps, APIs, or other operational solutions. Participate in demonstrations and production-readiness reviews. .Requirements: Must-Have Qualifications Active final Secret clearance. 7+ years of data science, machine learning, advanced analytics, or applied AI experience. 4+ years developing machine-learning solutions. Hands-on production AI/ML development experience. Strong Python and SQL skills. Experience delivering at least three substantive models or AI capabilities. At least one model personally taken from requirements through production or operational deployment. Experience with Azure AI/ML services or a comparable cloud environment. Ability to explain model evaluation, deployment, monitoring, and retraining. Strong experience with pandas, NumPy, scikit-learn, and at least one major ML/deep-learning framework. Experience with at least two of the following: Forecasting Anomaly detection Classification Recommendation engines Optimization Document extraction NLP, RAG, or GenAI Experience establishing measurable model-performance criteria. Experience with feature engineering, training, validation/test data, error analysis, explainability, and model documentation. Bachelor's degree in computer science, data science, statistics, mathematics, operations research, engineering, or related discipline, or equivalent specialized experience. Strongly Preferred Azure Machine Learning, Azure OpenAI, Azure AI Search, Microsoft Copilot, or comparable Azure AI services. Defense logistics, maintenance, readiness, fleet, supply-chain, acquisition, property, or financial analytics. GCSS-Army, SAP ECC, ERP, or maintenance-system data. Government-cloud or classified deployment experience. Model monitoring, drift detection, bias testing, red teaming, or human-in-the-loop validation. Integration of model outputs with Power BI, Power Apps, APIs, or operational applications. Experience presenting technical findings to operational users and senior leadership. About Xtreme Solutions XSI is a leading provider of information technology and professional services known for outstanding service delivery in a wide range of professional services engagements around the country. Team XSI continually meets and exceeds customer expectations. We are passionate about our work and making a difference. Our vision is to be the best professional services management company for both our customers and our employees. We need employees that share this vision. Our remarkable employees are the key to our company's incredible success. XSI promotes a work environment of trust, integrity, respect, continual improvement, customer satisfaction, and business success. We strive to provide a competitive salary and benefits, an engaging and rewarding work environment, and training and development opportunities. Equal Employment Opportunity Xtreme Solutions, Inc. is an Equal Opportunity Employer and federal contractor. All qualified applicants will receive consideration for employment without discrimination based on any status protected by applicable federal, state, or local law.As a federal contractor, Xtreme Solutions, Inc. takes affirmative action to employ and advance in employment qualified individuals with disabilities and protected veterans. We are committed to providing equal employment opportunities throughout all aspects of employment, including recruitment, hiring, promotion, compensation, training, and other terms and conditions of employment. Equal Opportunity Employer Individuals with Disabilities Protected Veterans

Job Description Job Description What Impact You'll Have GRVTY is seeking a motivated and experienced Data Manager to provide technical and managerial leadership over our overhead satellite imagery preprocessing operations. The ideal candidate is an experienced data operations leader with a passion for solving complex pipeline challenges, ensuring data integrity, and delivering mission-critical results in support of the DoW and Intelligence Community. This role serves as the primary communication interface between the customer and the team, translating requirements into successful execution across the full data operations lifecycle. What You'll be Owning Oversee and manage data, databases, and pipelines across the full data acquisition, curation, and preprocessing lifecycle, ensuring compliance with specified requirements and priorities Conduct regular Quality Control (QC) of data holdings to: Manage the data operations pipeline to include: Apply engineering best practices to optimize data pipeline efficiency and performance across all sensor modalities including: EO, FMV, HMI, and SAR Lead and manage team members by providing: Ensure data dictionaries, Entity Relationship Diagrams (ERDs), software comments, and documentation are regularly maintained and updated Serve as the primary customer communication interface to relay tasks and requirements and ensure successful work execution What You Must Have Active TS/SCI Clearance with the ability to obtain a CI/Poly People management experience, including: Team lead or project lead roles Independently initiating and driving projects to completion Strategic problem solver with excellent communication skills Experience in quantitative analysis and data operations, to include: Developing visualizations and processing complex data to create data-driven insights Data manipulation and ETL procedures Working knowledge of SQL and NoSQL database technologies Demonstrated experience managing databases and data pipelines Experience working with cloud architectures Experience working with large, complex geospatial data files and formats What Would be Nice to Have Experience using Agile/SAFe methodologies Experience with NGA enterprise technology systems such as NGA CORE and MLOps GEOINT Professional Certification - Fundamentals (F) Experience working with AI/ML technologies applied to geospatial data Pay Range: At GRVTY, we understand that compensation is influenced by many factors-such as geographic location, federal contract labor categories, wage rates, prior experience, skillsets, education, and certifications. We're proud to offer a work environment that empowers our team to achieve a strong work-life balance. GRVTY provides competitive pay, comprehensive benefits, and meaningful opportunities for professional growth. Our benefits package is designed to support the well-being of our employees and their families, and includes coverage in areas such as healthcare, financial wellness, retirement planning, family assistance, continued education, and paid time off. The pay range for this position is: $160,000 - $190,000 Pay Range: At GRVTY, we understand that compensation is influenced by many factors-such as geographic location, federal contract labor categories, wage rates, prior experience, skillsets, education, and certifications. We're proud to offer a work environment that empowers our team to achieve a strong work-life balance. GRVTY provides competitive pay, comprehensive benefits, and meaningful opportunities for professional growth. Our benefits package is designed to support the well-being of our employees and their families, and includes coverage in areas such as healthcare, financial wellness, retirement planning, family assistance, continued education, and paid time off. Virginia Pay Range $160,000-$190,000 USD Why Choose GRVTY The toughest national security challenges demand vision and ingenuity, not just resources. We deliver mission and technical expertise to outpace our adversaries. We're purpose-built to tackle the most entrenched, systemic national security issues around the world. We partner with our customers to help them overcome challenges in every corner of technology and defense-including the ones still being explored. Our growing capabilities create complementary advantages, giving on-the-ground operations the edge they need to succeed. We muster everything we have to answer every challenge presented, every day of our lives. At GRVTY, we believe that when our employees thrive, our company thrives. That's why we offer a comprehensive and competitive benefits package designed to support your well-being, growth, and work-life balance. • Robust health plan including medical, dental, and vision • Health Savings Account with company contribution • Annual Paid Time Off and Paid Holidays • Paid Parental Leave • 401k with generous company match • Training and Development Opportunities • Award Programs • Variety of Company Sponsored Events EEO Statement GRVTY, is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran and will not be discriminated against on the basis of disability. Anyone requiring reasonable accommodations should email or call with requested details. A member of the HR team will respond to your request within 2 business days. Know Your Rights: Workplace Discrimination is Illegal (eeoc.gov) Please review our current job openings and apply for the positions you believe may be a fit. If you are not an immediate fit, we will also keep your resume in our database for future opportunities.

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.

Job Description Job Description Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit . Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: The Head of Product Design will define and lead the user experience vision for Hivemind, Shield AI's autonomy development platform. This role is responsible for transforming complex autonomy, robotics, AI, and developer workflows into intuitive experiences that enable engineers, operators, and organizations to develop and deploy resilient autonomy at scale. A major focus of this role will be shaping the next generation of AI-native and agent-driven workflows across the autonomy lifecycle. As Hivemind evolves from traditional software tooling toward AI-assisted autonomy development, simulation, evaluation, deployment, and operations, this leader will help invent entirely new ways for users to collaborate with AI systems, agents, and foundation-model-powered tools. The ideal candidate has deep experience designing AI products, developer platforms, or complex technical systems and can translate emerging AI capabilities into workflows that dramatically improve user productivity and outcomes. This is a highly hands-on role as this leader will manage a team of elite designers. During the first 6-12 months, most of the time will be spent conducting user research, designing experiences, prototyping concepts, facilitating product discovery, and partnering directly with Product and Engineering teams to define the future of autonomy development. What you'll do:User Research & Product Discovery Lead customer research efforts across product development, customer engagement, and solutions teams to identify pain points, workflows, unmet needs, and product opportunities. Establish scalable mechanisms for gathering, synthesizing, and communicating user insights throughout the product development lifecycle. Translate customer and operational feedback into actionable product recommendations, requirements, and design initiatives. Product Design & User Experience Design end-to-end workflows across autonomy development, simulation, testing, analysis, deployment, and operations. Create intuitive experiences for highly technical users including autonomy engineers, software developers, operators, and mission planners. Simplify complex system architectures, data flows, infrastructure tooling, and AI workflows into understandable user experiences. Own the end-to-end experience of the product including training, documentation, tutorials, and overall workflows - help our users get the most of the product. Strategic Product Leadership Partner closely with Product Managers to shape product vision, roadmap priorities, and go-to-market strategies. Drive alignment across Product, Engineering, Design, and Executive Leadership through compelling narratives, prototypes, and visual storytelling. Advocate for user-centered decision making in a highly technical and engineering-driven environment. Design Practice, Systems & Organizational Scale Establish and evolve design standards, design systems, UX principles, and product design best practices across Shield AI. Raise the quality bar for product design, usability, consistency, and customer experience. Grow the product design function by mentoring a small team of designers, shaping design culture, and staying actively involved in critical design work. Champion design wins and impact across the organization, highlighting the important role design plays in delivering successful products. AI-Native Product Design & Agentic Workflows Define the future user experience for AI-assisted autonomy development, simulation, testing, deployment, and operational workflows. Design human-AI collaboration models that enable users to effectively leverage AI agents, copilots, and foundation-model-powered systems. Partner with Product, AI Research, and Engineering teams to create new interaction patterns for agent orchestration, autonomy generation, scenario creation, test generation, and mission planning. Develop frameworks for trust, transparency, explainability, and human oversight within AI-assisted workflows. Help establish industry-leading design patterns for Physical AI development platforms and agent-driven software systems. Required qualifications: 10+ years of experience in Product Design, UX Design, Human Factors, or related fields. Proven track record designing and shipping complex technical products, developer tools, platforms, infrastructure software, data-dense applications, or enterprise systems. Deep technical fluency and ability to effectively collaborate with senior engineering leaders on architecture, technical constraints, and software development workflows. Strong experience conducting user research and translating insights into product strategy and design solutions. Proven ability to influence product direction and organizational decisions without direct authority. Strong understanding of AI-powered product experiences, including conversational interfaces, human-in-the-loop workflows, AI-assisted decision making, and agent-based systems. Experience defining new user experiences in ambiguous technology spaces where industry standards and workflows are still emerging. Experience building and retaining high-performing design teams. Strong portfolio showcasing both strategic thinking and hands-on design execution. Preferred qualifications: Background designing developer platforms, SDKs, cloud infrastructure products, DevOps tooling, or engineering productivity tools. Direct work on AI/ML platforms, MLOps workflows, foundation-model-enabled products, copilots, or agentic systems. Familiarity with autonomy, robotics, simulation, digital twins, mission systems, physical AI, or related development workflows including testing, evaluation, deployment, and operations. Portfolio examples involving command-and-control systems, mission-planning interfaces, operational dashboards, or real-time decision-support tools. Ability to design across integrated hardware/software systems. Domain exposure to defense technology, aerospace, robotics, or other regulated, mission-critical, or high-consequence operational environments. San Diego, CA and Washington, D.C. pay range: $230,000 - $350,000 San Mateo, CA pay range: $280,000 - $420,000 Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 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.