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Job Title: Azure Cloud Engineer / Cloud Infrastructure Architect - Terraform & Security Location: Charlotte, NC / Jersey City, NJ / Plano, TX Duration: Contract - 12 months Pay Range: Charlotte NC (99.73 (Pay Rate: $70.23) Jersey City NJ (104.62 (Pay Rate: $73.67 Plano TX (104.62 (Pay Rate: $73.67 Job ID: 411708 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking a Azure Cloud Engineer / Cloud Infrastructure Architect - Terraform & Security to join our team. The ideal candidate will have strong experience in Microsoft Azure, Terraform, and cloud architecture and a proven ability to design, implement, and secure scalable cloud solutions aligned to enterprise cloud strategies. Responsibilities: Partner across technology teams to define and deliver cloud solutions aligned with the bank's cloud strategy. Perform product and solution design activities for cloud enablement. Design and implement new software and infrastructure solutions and enhance existing services. Ensure deliverables meet standards for accessibility, security, object-oriented practices, and performance. Author and execute unit and integration tests for infrastructure and application components. Collaborate with developers, QA, and project management to deliver high-quality outcomes. Participate in requirements elaboration, architecture reviews, and design sessions. Support hybrid work expectations with three days onsite per week. Required Skills & Qualifications: Infrastructure as Code with Terraform, including Terraform Enterprise, Private Module Registry, and Sentinel. Hands-on experience building and operating public cloud infrastructure. Primary skill: Microsoft Azure. Experience with AWS or GCP services. Deep knowledge of web protocols, operating systems, hypervisors, and distributed systems architecture. Azure Cloud Adoption Framework or similar frameworks expertise. Cloud security with Azure Policy, Microsoft Defender for Cloud, and Microsoft Sentinel. CI/CD toolchains such as Maven and Jenkins. General programming skills in Java and/or Python. Agile practices and test-driven development experience. Configuration management and automation with tools such as Ansible, Puppet, CloudFormation, or Salt. Minimum 7+ years of IT experience, including 5+ years in cloud engineering across Azure, AWS, or GCP. Preferred Skills: Identity management frameworks and tools experience. Linux/UNIX system administration. Container technologies such as Docker, Kubernetes, and OpenShift. Go programming language exposure. Cloud provider certifications such as Azure AZ-900. Experience architecting software solutions. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits Opportunities for growth with global clients A supportive, inclusive culture that values innovation and people Exposure to cutting-edge technologies and projects About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume. Please ensure one of the approved locations is listed on your resume. This role is hybrid with three days onsite per week.

Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. We handle relocation for anyone interested outside of the Hampton Roads, VA area Summary of Position (Job Purpose) This is an exciting opportunity to join the Data & Analytics Delivery Organization at Family Dollar. The company is undergoing a major transformation, and data driven insights are playing a critical role in delivering the best possible customer experience. We are seeking a Data Engineer who combines strong business acumen with hands on technical expertise. This role requires someone who can partner with key stakeholders to understand business challenges and translate them into world class technical solutions using modern cloud technologies. You will be responsible for designing and building data engineering solutions on our cloud based data platform. The role includes contributing to technical design, developing scalable data pipelines, and supporting data engineering workloads. Principal Duties and Responsibilities: Collaborate closely with stakeholders across product, architecture, development, business intelligence, and executive teams. Analyze data from multiple sources and develop solutions to integrate data into the enterprise data ecosystem Develop automated pipelines to ingest and process structured and unstructured data using both batch and streaming patterns with cloud native toolsets Work with diverse datasets and technologies to understand cross system correlations, patterns, and data relationships Build, schedule, and monitor data pipeline orchestrations Implement automation to optimize compute and storage usage across the cloud data platform Develop and enhance end to end monitoring and observability capabilities for cloud based data platforms Support knowledge sharing, cross training, and onboarding activities for team members Provide clear and frequent updates to stakeholders on progress, risks, and deliverables Participate in daily Scrum standups and contribute to an agile development environment Stay current on emerging trends and technologies in Data Warehousing and Analytics-particularly within retail. Minimum Requirements/Qualifications: Bachelor's degree or higher in Computer Science, Engineering, or a related field. 3+ years of experience in data engineering or data analytics. Strong understanding of RDBMS concepts with 3+ years of advanced SQL and data analysis experience. 2+ years of experience with Linux command line tools and scripting. 3+ years of Python development experience with expert level proficiency. 1+ year working with Big Data processing frameworks and tools. Hands on experience with GCP services such as Cloud Storage, Dataflow, Pub/Sub, and BigQuery. Strong proficiency in SQL, Python, Linux shell scripting, and data modeling. Solid knowledge of data modeling techniques Ability to analyze source systems and transform data to meet target data model requirements. Experience working with large scale data warehouses (10+ TB) and high volume ETL/ELT workloads (50M+ records/day). Demonstrated experience delivering end to end technical solutions within enterprise BI/Data Warehousing environments. Experience with performance tuning and optimization across the data delivery pipeline-from ingestion through analytics. Experience migrating data of various formats (JSON, delimited files, APIs, real time feeds) into Google BigQuery is strongly preferred. Experience working in a Scrum/Agile environment and tools such as Jira. Nice to have: Experience working with a data science workbench or ML development environment. Familiarity with data engineering aspects of machine learning pipelines (e.g., data prep, splitting, feature engineering, scoring) "Projected Salary Range: $95,000 - $118,500". 10% annual bonus opportunity This is not to be considered a complete list of job duties, as they may be amended or added to as needed. Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 Transportation Family Dollar

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. Position Summary The Endpoint User Computing Technical Product Manager owns the strategy, roadmap, lifecycle, adoption, and business outcomes for a portfolio of digital workplace products. The portfolio may include endpoint devices, Chrome Enterprise, Google Workspace, collaboration services, mobile experiences, virtual application delivery, endpoint management, secure access, employee productivity, and supporting workplace technologies. This position serves as the primary connection between employees, business stakeholders, architecture, engineering, operations, cybersecurity, service management, change management, finance, procurement, and strategic vendors. The Technical Product Manager converts workforce needs and technology opportunities into a prioritized product roadmap and ensures that products deliver measurable value, security, reliability, usability, and cost effectiveness. As a P4 Senior individual contributor, this role independently manages complex products, leads cross-functional prioritization, makes recommendations based on data and customer insight, and influences delivery across multiple teams without relying on direct organizational authority. Key Responsibilities Own and evolve the vision, strategy, value proposition, roadmap, and lifecycle for assigned endpoint and digital workplace products. Manage a product portfolio that may include Chromebooks, Windows and macOS devices, mobile devices, Google Workspace, Chrome Enterprise, endpoint management, secure browser, virtual applications, collaboration, printing, conferencing, and employee-access experiences. Gather and synthesize employee, business, operational, security, and technical requirements into product capabilities, outcomes, and roadmap priorities. Conduct customer research through interviews, surveys, telemetry, support trends, adoption data, and stakeholder feedback. Maintain the product roadmap, backlog, release plan, dependencies, risks, decisions, and measurable acceptance criteria. Prioritize capabilities using business value, employee impact, risk reduction, regulatory requirements, technical feasibility, lifecycle needs, and cost. Partner with the Endpoint User Computing Architect to ensure product direction aligns with target architecture, standards, security guardrails, and long-term technology strategy. Partner with engineering and operations teams to convert product outcomes into epics, features, user stories, technical requirements, and release plans. Define and monitor product KPIs covering adoption, experience, reliability, performance, service quality, support demand, security, cost, and business value. Manage product performance throughout its lifecycle, including introduction, adoption, enhancement, maintenance, vendor transition, and retirement. Ensure product plans address cybersecurity, privacy, accessibility, records management, audit, resiliency, and regulatory requirements. Lead stakeholder reviews, roadmap discussions, prioritization decisions, product demonstrations, release-readiness reviews, and retrospectives. Manage cross-product dependencies and coordinate with identity, network, cybersecurity, cloud, application, service desk, workplace, and business teams. Develop business cases and investment recommendations for new capabilities, renewals, migrations, modernization, and technical-debt remediation. Maintain cost transparency and help manage product budgets, forecasts, licensing, vendor commitments, and consumption. Manage strategic vendor relationships, performance commitments, roadmaps, escalations, and product-development opportunities. Lead product adoption and change activities in partnership with communications, training, support, and organizational-change teams. Use data and feedback to drive continuous improvement and ensure that product decisions remain centered on employee and business outcomes. Communicate product status, risks, value, dependencies, and decisions to technical, operational, and senior business stakeholders. Minimum Qualifications Bachelor's degree in information technology, computer science, business, engineering, product management, or a related discipline, or equivalent practical experience. Typically seven or more years of relevant professional experience, including technical product management, digital workplace, endpoint computing, collaboration technology, service management, or related fields. Demonstrated experience owning strategy, roadmaps, backlogs, releases, adoption, and lifecycle outcomes for complex enterprise technology products. Strong understanding of endpoint and digital workplace technologies, including device management, identity, collaboration, productivity, secure access, support, and employee experience. Experience working with Google Workspace, Chrome Enterprise, Chromebooks, or comparable enterprise productivity and endpoint platforms. Ability to translate business and employee needs into product outcomes, requirements, user stories, acceptance criteria, and prioritized delivery plans. Experience using quantitative and qualitative data to evaluate product adoption, service performance, customer experience, risk, and value. Understanding of Agile product delivery, backlog management, release planning, product discovery, and continuous improvement. Experience working with architecture, engineering, operations, cybersecurity, procurement, finance, service desk, and vendor teams. Strong stakeholder-management and communication skills, including negotiating trade-offs and presenting recommendations to senior leaders. Ability to manage multiple products, dependencies, and competing priorities in a complex enterprise environment. Preferred Qualifications Experience managing Google Workspace, Chrome Enterprise, endpoint, collaboration, or employee-experience products. Experience with Google Admin Console, Google Workspace reporting, Chrome device management, Gmail, Calendar, Drive, Meet, Chat, and associated security controls. Experience with Windows, macOS, mobile-device management, endpoint security, virtual applications, or identity platforms. Experience with Okta, GCP, endpoint-management platforms, service-management platforms, analytics, or digital-experience monitoring. Product management certification, Pragmatic Institute training, CSPO, SAFe Product Owner/Product Manager, or comparable credential. ITIL Foundation certification. Experience managing vendor contracts, licensing, product budgets, forecasts, and technology business cases. Experience supporting enterprise transformation, platform migration, organizational separation, or coexistence between productivity ecosystems. Experience in healthcare, regulated, or audit-sensitive environments. Success Measures Product roadmap execution and delivery of agreed business outcomes. User adoption, satisfaction, productivity, and digital employee-experience improvements. Product reliability, supportability, security, compliance, and service-performance results. Reduction in avoidable support demand, fragmented tools, technical debt, and duplicative capabilities. Transparent product cost, licensing utilization, vendor performance, and realized value. Effective coordination of architecture, engineering, operations, security, and business stakeholders. About MMS McKesson Medical-Surgical (MMS), which is expected to become Wellverse in early 2027, is a subsidiary and publicly reported segment of the McKesson Corporation. MMS distributes medical-surgical supplies, pharmaceuticals, diagnostic equipment and supplies, along with other solutions and services to virtually every type of healthcare setting and provider outside of the traditional hospital. These markets - often referred to as Alternate Care or Non-Acute Care - include physician offices, surgery centers, long-term care providers, laboratories, home health and hospice agencies, health systems, government facilities and online marketplaces and retailers. Alternate Care markets are growing rapidly, and MMS is proud to be a leader in this space. With a team of approximately 8,000 employees, a network of 15 distribution centers and approximately 900 delivery vehicles, we collaborate with more than 2,200 leading manufacturers and serve over 200,000 customer accounts across the U.S. Our catalog includes more than 270,000 SKUs of branded and private-label medical-surgical products - from bandages to specialty pharmaceuticals and COVID-19 tests. 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 . click apply for full job details

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. Position Summary The Endpoint User Computing Technical Product Manager owns the strategy, roadmap, lifecycle, adoption, and business outcomes for a portfolio of digital workplace products. The portfolio may include endpoint devices, Chrome Enterprise, Google Workspace, collaboration services, mobile experiences, virtual application delivery, endpoint management, secure access, employee productivity, and supporting workplace technologies. This position serves as the primary connection between employees, business stakeholders, architecture, engineering, operations, cybersecurity, service management, change management, finance, procurement, and strategic vendors. The Technical Product Manager converts workforce needs and technology opportunities into a prioritized product roadmap and ensures that products deliver measurable value, security, reliability, usability, and cost effectiveness. As a P4 Senior individual contributor, this role independently manages complex products, leads cross-functional prioritization, makes recommendations based on data and customer insight, and influences delivery across multiple teams without relying on direct organizational authority. Key Responsibilities Own and evolve the vision, strategy, value proposition, roadmap, and lifecycle for assigned endpoint and digital workplace products. Manage a product portfolio that may include Chromebooks, Windows and macOS devices, mobile devices, Google Workspace, Chrome Enterprise, endpoint management, secure browser, virtual applications, collaboration, printing, conferencing, and employee-access experiences. Gather and synthesize employee, business, operational, security, and technical requirements into product capabilities, outcomes, and roadmap priorities. Conduct customer research through interviews, surveys, telemetry, support trends, adoption data, and stakeholder feedback. Maintain the product roadmap, backlog, release plan, dependencies, risks, decisions, and measurable acceptance criteria. Prioritize capabilities using business value, employee impact, risk reduction, regulatory requirements, technical feasibility, lifecycle needs, and cost. Partner with the Endpoint User Computing Architect to ensure product direction aligns with target architecture, standards, security guardrails, and long-term technology strategy. Partner with engineering and operations teams to convert product outcomes into epics, features, user stories, technical requirements, and release plans. Define and monitor product KPIs covering adoption, experience, reliability, performance, service quality, support demand, security, cost, and business value. Manage product performance throughout its lifecycle, including introduction, adoption, enhancement, maintenance, vendor transition, and retirement. Ensure product plans address cybersecurity, privacy, accessibility, records management, audit, resiliency, and regulatory requirements. Lead stakeholder reviews, roadmap discussions, prioritization decisions, product demonstrations, release-readiness reviews, and retrospectives. Manage cross-product dependencies and coordinate with identity, network, cybersecurity, cloud, application, service desk, workplace, and business teams. Develop business cases and investment recommendations for new capabilities, renewals, migrations, modernization, and technical-debt remediation. Maintain cost transparency and help manage product budgets, forecasts, licensing, vendor commitments, and consumption. Manage strategic vendor relationships, performance commitments, roadmaps, escalations, and product-development opportunities. Lead product adoption and change activities in partnership with communications, training, support, and organizational-change teams. Use data and feedback to drive continuous improvement and ensure that product decisions remain centered on employee and business outcomes. Communicate product status, risks, value, dependencies, and decisions to technical, operational, and senior business stakeholders. Minimum Qualifications Bachelor's degree in information technology, computer science, business, engineering, product management, or a related discipline, or equivalent practical experience. Typically seven or more years of relevant professional experience, including technical product management, digital workplace, endpoint computing, collaboration technology, service management, or related fields. Demonstrated experience owning strategy, roadmaps, backlogs, releases, adoption, and lifecycle outcomes for complex enterprise technology products. Strong understanding of endpoint and digital workplace technologies, including device management, identity, collaboration, productivity, secure access, support, and employee experience. Experience working with Google Workspace, Chrome Enterprise, Chromebooks, or comparable enterprise productivity and endpoint platforms. Ability to translate business and employee needs into product outcomes, requirements, user stories, acceptance criteria, and prioritized delivery plans. Experience using quantitative and qualitative data to evaluate product adoption, service performance, customer experience, risk, and value. Understanding of Agile product delivery, backlog management, release planning, product discovery, and continuous improvement. Experience working with architecture, engineering, operations, cybersecurity, procurement, finance, service desk, and vendor teams. Strong stakeholder-management and communication skills, including negotiating trade-offs and presenting recommendations to senior leaders. Ability to manage multiple products, dependencies, and competing priorities in a complex enterprise environment. Preferred Qualifications Experience managing Google Workspace, Chrome Enterprise, endpoint, collaboration, or employee-experience products. Experience with Google Admin Console, Google Workspace reporting, Chrome device management, Gmail, Calendar, Drive, Meet, Chat, and associated security controls. Experience with Windows, macOS, mobile-device management, endpoint security, virtual applications, or identity platforms. Experience with Okta, GCP, endpoint-management platforms, service-management platforms, analytics, or digital-experience monitoring. Product management certification, Pragmatic Institute training, CSPO, SAFe Product Owner/Product Manager, or comparable credential. ITIL Foundation certification. Experience managing vendor contracts, licensing, product budgets, forecasts, and technology business cases. Experience supporting enterprise transformation, platform migration, organizational separation, or coexistence between productivity ecosystems. Experience in healthcare, regulated, or audit-sensitive environments. Success Measures Product roadmap execution and delivery of agreed business outcomes. User adoption, satisfaction, productivity, and digital employee-experience improvements. Product reliability, supportability, security, compliance, and service-performance results. Reduction in avoidable support demand, fragmented tools, technical debt, and duplicative capabilities. Transparent product cost, licensing utilization, vendor performance, and realized value. Effective coordination of architecture, engineering, operations, security, and business stakeholders. About MMS McKesson Medical-Surgical (MMS), which is expected to become Wellverse in early 2027, is a subsidiary and publicly reported segment of the McKesson Corporation. MMS distributes medical-surgical supplies, pharmaceuticals, diagnostic equipment and supplies, along with other solutions and services to virtually every type of healthcare setting and provider outside of the traditional hospital. These markets - often referred to as Alternate Care or Non-Acute Care - include physician offices, surgery centers, long-term care providers, laboratories, home health and hospice agencies, health systems, government facilities and online marketplaces and retailers. Alternate Care markets are growing rapidly, and MMS is proud to be a leader in this space. With a team of approximately 8,000 employees, a network of 15 distribution centers and approximately 900 delivery vehicles, we collaborate with more than 2,200 leading manufacturers and serve over 200,000 customer accounts across the U.S. Our catalog includes more than 270,000 SKUs of branded and private-label medical-surgical products - from bandages to specialty pharmaceuticals and COVID-19 tests. 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 . click apply for full job details

Machine Learning Engineer 5 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 5 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 5 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 5 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Edward Jones is seeking an Engineer III to design, build, and optimize secure, scalable technology solutions that support our core finance and insurance platforms. In this role, you will lead complex application and integration projects, collaborate with product, security, and operations teams, and drive best practices in software engineering and cloud architecture. You will mentor junior engineers, improve reliability and performance of critical systems, and help modernize legacy applications, enabling our financial advisors to deliver client-first, long-term investment and retirement planning services. Responsibilities Design, develop, and maintain scalable applications supporting financial and insurance services Lead complex engineering projects from requirements through deployment and support Collaborate with product, security, and operations to define technical solutions and standards Implement secure coding, testing, and deployment best practices Optimize system performance, reliability, and observability for critical platforms Modernize and refactor legacy applications and services to modern architectures Develop and integrate APIs and data services for internal and external systems Mentor and provide technical guidance to junior and mid-level engineers Participate in code reviews and enforce engineering quality standards Contribute to technical roadmaps and continuous improvement initiatives Required Skills Object-oriented programming (e.g., Java, C#, or similar) Cloud platforms (AWS, Azure, or GCP) RESTful API design and integration Relational and/or No SQL databases CI/CD pipelines and Dev Ops practices Containerization (Docker, Kubernetes) Automated testing and test frameworks Monitoring, logging, and observability tools Secure software development practices System architecture and design patterns

Edward Jones is seeking an Engineer III to design, build, and optimize secure, scalable technology solutions that support our finance and insurance platforms. In this role, you will lead complex application and integration projects, translate business and compliance requirements into technical designs, and mentor junior engineers. You will collaborate closely with product, security, and operations teams to deliver resilient, high availability systems that power client-facing tools, analytics, and back office services, while championing best practices in coding, testing, DevOps, and cloud engineering. Responsibilities Design and develop secure, scalable applications and services for finance and insurance platforms Translate business and regulatory requirements into robust technical solutions Lead complex engineering projects and provide technical direction to teams Implement and maintain CI/CD pipelines and Dev Ops practices Ensure system reliability, performance, and high availability Collaborate with product, security, and operations teams on solution design Conduct code reviews and enforce engineering best practices and standards Mentor and coach junior and mid level engineers Implement automated testing and quality assurance practices Contribute to cloud architecture and modernization initiatives Required Skills Software development (Java, C#, or similar OO language) Cloud platforms (AWS, Azure, or GCP) RESTful APIs and microservices architecture SQL and relational databases CI/CD tools (e.g., Jenkins, Git Hub Actions, Azure Dev Ops) Infrastructure as Code (e.g., Terraform, Cloud Formation) Automated testing frameworks (unit, integration, performance) Containerization and orchestration (Docker, Kubernetes) Secure coding and application security practices Monitoring and observability tools (e.g., Splunk, New Relic, Datadog)

Job Description Job Description CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . What You'll Do: The Data Services Team builds and operates the data platform powering CoreWeave's AI cloud, from transactional and analytical databases to streaming, metadata, and governance. We give customers and CoreWeave engineers the primitives to ingest, store, process, and serve data with the latency, throughput, and elasticity that AI training, inference, and agentic workloads demand. If you want to shape how data powers a rapidly scaling AI cloud, and build infrastructure that AI applications depend on, this is your team. About the role: As a Staff Product Manager for Data Services, you'll own strategy, roadmap, and execution across CoreWeave's data services portfolio, with particular emphasis on transactional (OLTP) and analytical (OLAP) platforms, alongside streaming, data lakes, and integration. You'll shape a multi-year vision for how our services support AI training, inference, and agentic applications, then lead delivery from 0 to 1 and beyond. You'll work directly with customers and engineering to identify opportunities, prioritize investments, differentiate our offerings, and deliver reliable, scalable data infrastructure. The hardest challenges involve rapid provisioning, data access, throughput, and performance for GPU-intensive and agentic workloads, with meaningful influence over technical direction and customer outcomes. In this role, you will own: Product strategy and roadmap across transactional and analytical Data Services, balancing immediate customer needs with broader portfolio investments Customer and partner engagement, understanding data architectures, validating opportunities, and translating requirements into differentiated services and solutions Cross-functional collaboration with engineering, GTM, and leadership to prioritize investments, resolve tradeoffs, and accelerate delivery Market and competitive analysis to evaluate alternatives, identify customer value, and justify product investments through measurable business outcomes API-first platform thinking, partnering with architects on scalability, reliability, service interfaces, and performance for AI workloads Who You Are: 8+ years of product management experience in data platforms or cloud infrastructure, including 3-4 years owning customer-facing managed databases, analytical engines, or data services Technical fluency in: Transactional and/or analytical databases (e.g., PostgreSQL, MySQL, Aurora, Snowflake, BigQuery), including workload requirements, performance, and scalability Streaming and pipelines (e.g., Kafka, CDC, ETL/ELT, lakehouse architectures, data ingestion and processing) Data security and governance (encryption, IAM/RBAC, tenant isolation, data locality, compliance) Demonstrated ownership of external, API-first Data Services from concept through launch, adoption, and multiple release cycles Strong product judgment, translating customer needs into differentiated capabilities, strategic priorities, and measurable business outcomes Comfort navigating ambiguity, making technical and commercial tradeoffs, and executing quickly in evolving AI infrastructure markets Preferred: Staff or Principal PM experience at a database vendor, cloud provider, or high-growth infrastructure company Direct ownership of managed transactional or analytical services on AWS, Azure, or GCP (e.g., RDS, Aurora, Cosmos DB, BigQuery) Experience with distributed database architectures, replication, workload isolation, elastic scaling, and performance optimization Experience supporting AI training, inference, or agentic workloads through vector search, rapid provisioning, analytical processing, or data serving Familiarity with cloud service differentiation, consumption-based pricing, product economics, and customer adoption Prior engineering or architecture experience with databases, query engines, or distributed systems Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams - even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. Love building data services that customers and engineers depend on for critical AI workloads Are curious about transactional, analytical, and emerging AI data patterns, separating meaningful customer value from hype Can define product strategy across technical domains and align engineering, customers, and business stakeholders Enjoy working directly with customers to understand workloads, evaluate alternatives, and identify meaningful product opportunities Balance strategic vision with rapid execution, measurable outcomes, and pragmatic decisions under uncertainty Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: Be Curious at Your Core Act Like an Owner Empower Employees Deliver Best-in-Class Client Experiences Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Flexible Spending Account Health Savings Account Tuition Reimbursement Ability to Participate in Employee Stock Purchase Program (ESPP) Mental Wellness Benefits through Spring Health Family-Forming support provided by Carrot Paid Parental Leave Flexible, full-service childcare support with Kinside 401(k) with a generous employer match Flexible PTO Catered lunch each day in our office and data center locations A casual work environment A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. 1157, or (iv) asylee under 8 U.S.C. 1158, (B) eligible to access the export controlled information without a required export authorization . click apply for full job details

Vantor seeks a Constellation Integration Program Manager to lead complex software and data integration initiatives for modern web and cloud solutions. You'll own program delivery from discovery through rollout, aligning client goals with technical roadmaps, APIs, and data flows. Partnering with engineering and stakeholders, you'll coordinate agile teams, manage dependencies and risk, and ensure scalable, secure architectures. You'll promote integration standards, automation, and reusability while communicating progress clearly and driving measurable results in a collaborative, low-ego culture focused on learning and impact. Responsibilities Lead end-to-end delivery of Constellation integration programs for client software ecosystems Translate client business goals into technical integration roadmaps and milestones Coordinate cross-functional teams including developers, data engineers, and QADesign, document, and govern integration architectures, APIs, and data flows Manage schedules, risks, dependencies, and budgets using agile practices Establish integration standards, KPIs, and quality benchmarks Partner with clients to gather requirements, run demos, and manage expectations Ensure secure, scalable, and resilient integrations across cloud environments Drive continuous improvement, automation, and reusability of integration components Prepare status reports and communicate progress to stakeholders and leadership Required Skills Program management Systems integration API design and management Cloud platforms (AWS/Azure/GCP) Data mapping and ETLAgile/Scrum delivery Technical requirements analysis Risk and dependency management Integration architecture Stakeholder communication

Vantor is hiring a Staff Systems Engineer to lead architecture and product engineering for modern web and data driven solutions. You will design scalable, cloud native systems, guide implementation across services, APIs, and infrastructure, and ensure reliability, security, and performance. Partnering closely with product and client stakeholders, you'll translate business needs into technical roadmaps, run architecture reviews and PoCs, and mentor engineers in craftsmanship and automation. This role suits a hands on technical leader who enjoys complex systems, agile delivery, and collaborating in a low ego, learning focused environment. Responsibilities Lead design and evolution of large scale distributed systems and cloud architectures for client products Collaborate with product managers to translate business needs into technical roadmaps and system designs Define and enforce engineering standards, reliability, security, and performance best practices Guide end to end implementation across backend, APIs, integrations, and infrastructure automation Conduct architecture reviews, technical spikes, and Po Cs for new platforms and services Mentor engineers, provide code and design reviews, and champion craftsmanship and automation Partner with clients in agile ceremonies to refine requirements and validate technical approaches Own production readiness, monitoring, and incident response strategies for critical systems Evaluate and select tools, platforms, and cloud services aligned to project and client goals Contribute to continuous improvement of engineering processes and documentation Required Skills Systems architecture and solution design Cloud platforms (AWS, Azure, or GCP) Distributed systems and microservices Infrastructure as Code (Terraform, Cloud Formation, or similar) API design and integration (REST/Graph QL) Backend development (e.g., Node.js, Java, . NET, Go, or similar) Containerization and orchestration (Docker, Kubernetes) CI/CD pipelines and Dev Ops practices Monitoring, observability, and reliability engineering Relational and No SQL databases

As a Deployment Strategist at Vantor, you'll lead the rollout of custom software and data-driven solutions that help clients modernize systems and streamline operations. You'll partner directly with stakeholders to understand goals, shape deployment strategies, and translate technical capabilities into business outcomes. Working in agile, cross-functional teams, you'll coordinate implementation across web, automation, and cloud platforms, oversee configuration and testing, and guide change management and user adoption. This role blends technical fluency, systems thinking, and client-facing collaboration in a culture that values craftsmanship, ownership, and continuous learning. Responsibilities Partner with clients to understand business goals and translate them into deployment strategies for custom software solutions. Plan and lead end-to-end deployment of modern web, automation, and cloud-based products. Configure, test, and validate solutions in client environments to ensure performance, reliability, and security. Collaborate with engineers, product managers, and data specialists in agile delivery teams. Develop rollout plans, training, and documentation to drive user adoption and change management. Monitor post-deployment performance, analyze metrics, and recommend continuous improvements. Facilitate workshops and demos to align stakeholders and gather deployment feedback. Identify risks and dependencies, and manage deployment timelines and expectations. Required Skills Software deployment planning Cloud platforms (AWS/Azure/GCP) Modern web application architectures Automation and CI/CD pipelines SQL and data integration Systems analysis and requirements translation Agile/Scrum delivery practices Technical documentation Monitoring and observability tools Change management and user training

Job Description Job Description Role Overview The Principal Data Engineer is a senior technical authority responsible for defining the organization's data architecture, setting long-term technical strategy, and solving the most complex data engineering challenges. This role influences company-wide data standards, mentors senior engineers, and partners with executive and cross-functional leaders to ensure data platforms scale with the business. Key Responsibilities Define and evolve the long-term data architecture and technical vision Design highly scalable, resilient data platforms and pipelines Set standards for data modeling, reliability, observability, and governance Lead complex, high-risk technical initiatives and migrations Serve as the escalation point for critical data incidents and root cause analysis Influence tool selection and technology adoption across the data stack Mentor Staff and Senior Data Engineers and elevate engineering excellence Partner with leadership to align data strategy with business goals Ensure data platforms support analytics, ML, and product use cases at scale Qualifications Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience) 10+ years of experience in data engineering or related disciplines Expert-level SQL and strong proficiency in Python or similar languages Deep experience with data warehousing, data lakes, and distributed systems Proven track record of designing and operating large-scale data platforms Strong systems thinking and architectural decision-making skills Preferred Experience Cloud platforms (AWS, Azure, or GCP) Streaming and real-time systems (Kafka, Spark, Flink, etc.) Advanced data governance, security, and compliance practices Supporting ML, AI, or product-led data platforms Influencing technical direction without direct managerial authority

Job Description Job Description CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . What You'll Do CoreWeave is seeking a Security Engineer to spearhead the design, deployment, and integration of Wireless Intrusion Detection Systems (WIDS) across our rapidly expanding global physical security network, standardized on the Bastille Networks wireless airspace cybersecurity platform. This role is built for a technical owner with deep expertise in RF spectrum monitoring, wireless threat detection, and the integration of WIDS telemetry into enterprise security platforms. They will lead the charge in detecting rogue access points, rogue cell towers, unauthorized wireless devices, and RF-based threats across our data center estate, and surfacing those events into our centralized security operations. The ideal candidate brings a blend of sophisticated networking and RF skills, hands-on experience with the Bastille platform and sensor arrays, a mastery of the Genetec Security Center ecosystem, a proven ability to integrate complex third-party systems within Azure or GCP environments, and an understanding of wireless threat detection best practices and how to deploy them at scale. We are looking for a collaborative, customer-centric engineer who pairs technical administration expertise with the ability to produce high-quality technical documentation and results. This role is based out of any of our hub locations. The position requires up to 20% travel - including international assignments for on-site project execution - and flexibility for after-hours support to ensure the continuous monitoring of our global operations. About the Role Design, deploy, and maintain the Bastille Networks WIDS platform and sensor arrays across CoreWeave's data center facilities, offices, and PoP sites in support of our Global Security Operations Center (GSOC). Architect and implement the integration of Bastille wireless detection telemetry into the Genetec Security Center ecosystem, translating wireless threat events into actionable alarms, events, and event-to-actions within Security Desk via API/SDK, syslog, or middleware as required. Deploy and tune Bastille RF spectrum monitoring to detect and localize rogue access points, rogue cell towers, unauthorized wireless devices, Bluetooth/BLE and IoT threats, and other RF-based risks across 50+ wireless protocols. Conduct RF site surveys and design sensor placement and coverage plans to ensure accurate device localization across each facility's airspace. Support the configuration and hardening of Bastille sensors, concentrators, and supporting server/cloud infrastructure, ensuring alignment with published standards and industry best practices. Develop and maintain a comprehensive library of WIDS documentation, including sensor placement plans, RF coverage/heat maps, integration architecture diagrams, and troubleshooting playbooks. Create, uphold, and maintain change management processes, ensuring all Bastille configuration and integration changes are meticulously documented, tested, and approved. Establish alerting and escalation workflows so GSOC operators receive, triage, and respond to wireless intrusion events through Genetec and unified security tooling. Maintain an audit-ready inventory of authorized and unauthorized wireless devices, supporting shadow-IT elimination and regulatory compliance evidence. Perform technical root cause analysis for false positives, sensor coverage gaps, and detection failures, implementing corrective actions to improve detection fidelity. Collaborate with network, IT security, and SOC teams to correlate Bastille detections with broader wireless security posture, CAASM/XDR/Zero Trust tooling, and threat intelligence. Who You Are 5+ years of experience in Physical Security Engineering, Network Engineering, wireless/RF security, or a related technical infrastructure role. Hands-on experience deploying and operating Wireless Intrusion Detection/Prevention Systems (WIDS) and RF spectrum monitoring platforms; direct experience with the Bastille Networks platform and sensor arrays strongly preferred. Advanced expertise in the Genetec Security Center platform, including Directory, Archiver, and Synergis roles, as well as event-to-action, alarm management, and API/SDK integrations for ingesting third-party telemetry. Strong understanding of wireless protocols and standards (802.11 a/b/g/n/ac/ax, Bluetooth/BLE, Zigbee, cellular), RF fundamentals, and common wireless attack vectors (rogue APs, rogue cell towers, evil-twin, deauthentication, wireless exfiltration). Strong knowledge of Windows Server environments, including deployment, maintenance, and system hardening. Solid understanding of networking fundamentals (TCP/IP, routing, VLANs) and SQL databases, including data integrity management and troubleshooting. Proven experience integrating third-party systems and deploying field solutions in collaboration with external vendors. Ability to communicate complex technical concepts clearly to non-technical audiences, with strong written and verbal communication skills. Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field. Demonstrated ability to work independently with strong attention to detail and follow-through. Preferred Certifications: GSEC, Security+, Network+, CCNA, CWNA/CWSP (Certified Wireless Security Professional), CISSP, or manufacturer certifications (Bastille, Genetec, Axis, Hanwha, Bosch). Specialized Experience: Prior Bastille deployment or administration experience; experience deploying WIDS in enterprise or AI/data center environments, performing RF site surveys, and integrating wireless detection telemetry into a PSIM, SIEM, or Genetec Security Center. Industry Context: Familiarity with wireless security controls for data center physical security, Bastille integrations with platforms such as Axis, Splunk, Cisco, and Lenel, and relevant compliance frameworks (ISO 27001, SOC2). Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: Be Curious at Your Core Act Like an Owner Empower Employees Deliver Best-in-Class Client Experiences Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! The base salary range for this role is $122,000 to $179,000. The starting salary will be determined by job-related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Flexible Spending Account Health Savings Account Tuition Reimbursement Ability to Participate in Employee Stock Purchase Program (ESPP) Mental Wellness Benefits through Spring Health Family-Forming support provided by Carrot Paid Parental Leave Flexible, full-service childcare support with Kinside 401(k) with a generous employer match Flexible PTO Catered lunch each day in our office and data center locations A casual work environment A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race . click apply for full job details

Job Description Job Description Palo Alto Firewall Engineer / SME (PCNSE) Cyber Security Engineering Specialist III - Firewall Services Location: Springfield, VA - on site Time Type: Full time, Exempt Clearance Required to Start: Active TS/SCI (U.S. citizenship required) Additional Requirement: Must be able to obtain and maintain a U.S. Government polygraph Travel: Up to 15%, local and CONUS Salary Range: $117,000 - $128,000 Own the Palo Alto estate - legacy iron through Prisma and Panorama. RISA is hiring a Palo Alto SME to be the focal point for every Palo Alto task, operation, and project on the Network Security Services team supporting an Intelligence Community customer. The work spans both ends of the estate: PA-3000 and PA-5000 hardware refreshes and legacy CLI on one side, Prisma Access, VM-Series, and Cortex on the other. You will talk to the owner here, not a recruiting queue. What You Will Do Serve as the lead technical authority for administering, configuring, and troubleshooting Palo Alto NGFWs across a hybrid enterprise. Lead the design, analysis, testing, and implementation of secure network architectures on the Palo Alto stack. Manage the full hardware and software lifecycle, including complex refreshes and PAN-OS upgrades on legacy platforms. Run Panorama for centralized policy management across a fleet of physical and virtual firewalls. Configure master-level security profiles - App-ID, User-ID, Content-ID, SSL Decryption, and WildFire. Own configuration management processes and SOPs for all Palo Alto platforms. Mentor junior engineers and act as the escalation point for complex troubleshooting. Liaise with contract, customer, and government DAA on network security status, policies, and procedures. What You'll Bring S. citizenship and an active TS/SCI. Ability to successfully obtain and maintain a U.S. Government polygraph. Education and experience, per the contract labor category criteria: Bachelor's degree in a field applicable to the position plus 6 years of relevant experience. Equivalents accepted - Master's plus 4, Associate's plus 8, or High School diploma/GED plus 10. 7+ years hands-on administering, configuring, and troubleshooting Palo Alto NGFWs in large-scale enterprise or global environments. Active PCNSE certification. DoD 8140.01 and 8570.01-M IAT Level II (e.g. Security+ CE), and CSSP Infrastructure Support within 120 days of start. Deep practical knowledge of legacy Gen 2/Gen 3 hardware - PA-3000 and PA-5000 series, legacy CLI, physical troubleshooting, line-card replacement. Prisma Access (SASE), Prisma SD-WAN, and VM-Series in AWS, Azure, or GCP. Panorama template and device-group inheritance across a hybrid fleet. Advanced BGP, OSPF, IPSec VPN, and NAT. Nice to Have PCNSC or Prisma Certified SASE Professional (PCSAE). Python, plus firewall automation with Ansible, Terraform, or the Palo Alto XML/REST APIs. Cortex XDR or XSOAR; Expedition for legacy rule migration to App-ID policy. Zero Trust Network Access architecture; F5 (APM, AFM), Juniper SRX, or Cisco FTD/ASA. About RISA Rolston Information Systems Assurance (RISA) is a Service-Disabled Veteran-Owned Small Business that has supported federal defense and intelligence cybersecurity missions for more than seventeen years. We are small on purpose: direct access to leadership, a real say in how the work gets done, and none of the layers that slow large primes down. Benefits Medical, dental, and vision insurance; 401(k) and Roth; Paid Time Off; and 11 paid Federal Holidays. RISA is an Equal Opportunity Employer. Upon receiving an offer of employment, all applicants will be required to do a background check, including a criminal record check and employment/education verification.

Edward Jones seeks an Application Security Architect to design, implement, and govern secure application architectures for a leading finance and insurance firm. In this role, you will define security standards, integrate security into SDLC and DevOps pipelines, conduct threat modeling and secure code reviews, and guide teams in remediating vulnerabilities across cloud and on prem applications. You'll partner with engineering, risk, and compliance to ensure regulatory alignment and client data protection. Edward Jones offers a collaborative, client first culture, strong support for professional growth, and opportunities to influence enterprise security strategy. Responsibilities Design and maintain secure application and cloud architectures Define and enforce application security standards and best practices Integrate security controls into SDLC and CI/CD pipelines Perform threat modeling and application security risk assessments Conduct secure code reviews and oversee vulnerability remediation Collaborate with engineering, risk, and compliance teams on security requirements Align application security with regulatory and industry standards Provide security guidance, mentoring, and training to development teams Evaluate and implement security tools and technologies Contribute to enterprise security strategy and roadmap Required Skills Application security architecture Secure SDLC practices Threat modeling Secure code review CI/CD and Dev Sec Ops integration Cloud security (AWS/Azure/GCP) Web and API security (OWASP Top 10) Security tooling (SAST/DAST/IAST/SCA) Identity and access management Regulatory and compliance knowledge (PCI-DSS, SOX)

Edward Jones seeks an experienced Engineer IV to design, build, and optimize enterprise-scale technology solutions supporting our finance and insurance platforms. In this role, you will architect secure, resilient systems, lead complex projects from concept through production, and mentor engineers while collaborating with cross-functional partners. You will drive modernization, automation, and data integration efforts that enhance client-facing tools and advisor productivity. Ideal candidates bring deep technical expertise, strong communication, and a passion for delivering reliable, high-quality solutions in a highly regulated industry. Responsibilities Architect and design scalable, secure enterprise systems for finance and insurance platforms Lead end-to-end delivery of complex technology projects Develop and review high-quality code, tests, and documentation Implement integration, APIs, and data pipelines supporting business workflows Drive modernization, cloud adoption, and automation initiatives Ensure solutions meet security, compliance, and reliability standards Troubleshoot and resolve production issues, improving observability and performance Collaborate with product, security, and business stakeholders to refine requirements Mentor and coach junior and mid-level engineers Contribute to engineering best practices, standards, and technical roadmaps Required Skills Enterprise software architecture and design Java, C#, or similar object-oriented programming language RESTful APIs and microservices SQL and relational databases; exposure to No SQL or cloud-native data stores Cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes) CI/CD pipelines and Dev Ops practices Security, compliance, and identity/access management in regulated environments Observability tools (logging, metrics, tracing) and performance tuning Automated testing (unit, integration, regression) Data integration and ETL pipelines

Edward Jones seeks an Application Security Architect to design and implement secure application architectures for a leading finance and insurance firm. You will define security patterns, conduct threat modeling, review designs and code, and guide development teams to build secure, resilient systems that protect client data and financial transactions. Partnering with architecture, engineering, risk, and compliance, you'll champion secure SDLC practices, evaluate security tools, and drive remediation of vulnerabilities. This role offers growth, influence on enterprise security strategy, and the chance to support clients' long-term financial goals. Responsibilities Design and maintain secure application architectures and patterns Lead threat modeling and risk assessments for key applications Perform security design and code reviews with development teams Define and promote secure SDLC standards and best practices Evaluate, implement, and tune application security tools (SAST/DAST/SCA) Collaborate with architecture, engineering, risk, and compliance teams Provide security guidance for cloud-native and API-based solutions Drive remediation of vulnerabilities and track risk reduction Develop security reference architectures and technical standards Mentor engineers on application security concepts and practices Required Skills Application security architecture Threat modeling Secure SDLCSecure coding (Java/. NET/Java Script or similar) SAST/DAST/SCA tooling API and microservices security Cloud security (AWS/Azure/GCP) Identity and access management (OAuth2/OIDC) Vulnerability management and remediation Security standards and frameworks (OWASP, NIST)