304 jobs found

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 . Role Overview CoreWeave is seeking an experienced Network Security Engineer for our network security initiatives to help protect our rapidly scaling cloud infrastructure hosting high-performance AI workloads. In this role, you will architect and implement cutting-edge security solutions focused on network security across our data center perimeter and internal networks. You will work in a high-scale environment (CoreWeave is positioning itself as the next major hyperscaler) and ensure our network and services remain secure, resilient, and trustworthy. The ideal candidate is a seasoned security expert (3-7 years experience) with a deep understanding of modern cloud/network architectures and a passion for educating cross-functional partners in a security-first culture. Key Responsibilities Network Security Architecture: Design and deploy robust security measures across the network perimeter and internal fabrics (e.g., firewalls, IPS/IDS, segmentation, configuration health, best practicies) to protect CoreWeave's globally distributed hyperscale infrastructure hosting large-scale AI workloads. Ensure that all entry points, high-speed interconnects, and cloud services are fortified against unauthorized access and attacks. Zero Trust Implementation: Champion a Zero Trust security model across CoreWeave's network and cloud environments. Architect solutions that enforce least-privilege access, continuous verification, and micro-segmentation of services - ensuring no implicit trust at any layer. Security Monitoring & Incident Response: Establish robust monitoring for network security events and potential breaches across high-density AI cluster networks. Proactively identify vulnerabilities or indicators of compromise, and coordinate incident response efforts for any network-related security incidents to minimize impact. Cross-Functional Collaboration: Work closely with Networking, Infrastructure, and Software Engineering teams to integrate security best practices into architecture, deployments, and processes. Provide expert guidance during design and code reviews to ensure new services and features are secure by design. AI Infrastructure & Interconnect Security: Secure high-density GPU clusters and ultra-low latency backend fabrics. Implement security controls to protect customer data in transport. Leadership & Education: Contribute to security initiatives and foster a security-first mindset across the organization. Educate partners in other teams on network security principles, conduct security training sessions, and lead by example in following and enforcing security policies and standards. Policy Enforcement: Help refine, implement, and enforce security policies and standard operating procedures for a highly scalable, distributed environment. Regularly review network and cloud security postures, ensuring compliance with industry best practices and adapting policies as the company grows. Required Qualifications Experience: 3-7 years of hands-on experience in network security engineering, with exposure to large-scale cloud or hyperscaler environments. Proven track record protecting complex, distributed systems at scale. Network Security Expertise: Deep understanding of network security principles and technologies - including experience mitigating DDoS attacks, securing high-speed data center fabrics, defending against web exploits, and implementing zero trust methodologies. Cloud & Network Architecture: Strong conceptual and practical knowledge of securing modern cloud and network architectures. Proficient in network protocols (TCP/IP, DNS, BGP, HTTP/S, etc.), network segmentation, VPNs, and firewall configurations. Experience securing cloud platforms (AWS, GCP, Azure or custom hyperscale infrastructure) and containerized environments. Security Contributions: Demonstrated ability to contribute key input to security initiatives and projects end-to-end. Experience educating peer engineers and partner teams, with a talent for instilling a security-first mindset across diverse teams. Cross-Team Collaboration: Excellent communication and collaboration skills. Ability to work closely with cross-functional teams (Networking, Infrastructure, DevOps/SRE, Software) to design and implement security solutions that enable the business while protecting critical assets. Policy and Compliance: Experience in implementing, refining, and enforcing security policies and controls for highly scalable, distributed systems. Familiarity with industry standards and compliance frameworks (e.g., NIST, ISO 27001, SOC2) and how they apply in a cloud environment. Preferred Skills & Qualifications Hyperscaler Environment: Prior experience working in a top-tier cloud provider or hyperscale environment is a strong plus (FAANG or similar organization). Understanding of the unique security challenges at massive scale. Zero Trust & Identity: Experience designing zero trust networks, including identity and access management (IAM) systems, single sign-on, multi-factor authentication, and network access control solutions. Automation & Scripting: Proficiency in scripting or programming (Python, Go, or similar) for automating security tasks, integrating security tools, and handling infrastructure-as-code. Experience with DevSecOps practices and CI/CD pipeline security is a plus. Security Certifications: Relevant certifications such as CISSP, CCSP, GIAC (GSEC, GCIH, etc.), or cloud security certifications (AWS/Azure Security Specialty) are advantageous, demonstrating a strong foundation in security best practices. Continuous Learning: Active involvement in the security community or contributions to open-source security projects. Up-to-date knowledge of the latest threats, vulnerabilities, and mitigation strategies in network and cloud security. The base salary range for this role is $153,000 to $204,000. 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 . click apply for full job details

Job Description Job Description Benefits: Onsite Competitive salary Opportunity for advancement About the Role: Select Minds LLC is looking for a talented Network Security Engineer to join our growing team in Dallas, TX. This is an exciting opportunity to protect critical infrastructure, design robust security solutions, and work alongside a team of passionate technology professionals. If you thrive in a fast-paced environment and love solving complex security challenges, we want to hear from you! Responsibilities: Design, implement, and maintain network security architectures, firewalls, and intrusion detection/prevention systems (IDS/IPS) Monitor network traffic for suspicious activity and respond to security incidents and threats in real time Perform vulnerability assessments, penetration testing, and risk analysis across network infrastructure Configure and manage VPNs, access control lists (ACLs), and zero-trust network policies Collaborate with IT and DevOps teams to ensure security best practices are integrated into all systems Develop and maintain security documentation, policies, and incident response procedures Stay current with emerging cybersecurity threats, trends, and compliance requirements (NIST, ISO 27001, etc.) Requirements: 3+ years of experience in network security engineering or a related cybersecurity role Proficiency with firewalls, SIEM tools, and network monitoring platforms (e.g., Cisco, Palo Alto, Splunk) Strong understanding of TCP/IP, DNS, VPN, and network protocols Experience with cloud security environments (AWS, Azure, or GCP) is a plus Relevant certifications such as CISSP, CCNP Security, CEH, or CompTIA Security+ preferred Strong analytical and problem-solving skills with keen attention to detail Excellent communication skills and ability to work both independently and collaboratively About Us: Select Minds LLC is a forward-thinking technology firm based in Dallas, TX, dedicated to delivering innovative IT and security solutions to businesses of all sizes. Our clients trust us to safeguard their most critical assets, and our team takes that responsibility seriously. We foster a culture of continuous learning, collaboration, and growth - making Select Minds a place where talented professionals truly thrive.

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." General Summary: The Manager of Vendor Governance, FinOps, Asset Management & Contract Management serves as the centralized control-plane governance function within Family Dollar's Infrastructure Engineering organization. This is a unique, high-trust role designed with intentional independence - operating without dedicated direct reports to preserve separation of duties, eliminate conflicts of interest, and ensure objective oversight across all infrastructure engineering teams and BPO partners. This role provides the VP of Infrastructure Engineering & Operations with an independent, consolidated view of vendor performance, technology spend, asset health, and contractual obligations across all domains: Hybrid Cloud, Network Engineering, Automation, and Retail/Edge environments. It is the single source of truth for governance intelligence across a multi million infrastructure portfolio spanning 7,400+ stores, 9 distribution centers, 2 data centers, and 3 public cloud platforms. This is not an operational role. It is a governance, intelligence, and accountability function - one that provides executive-level visibility and keeps the infrastructure organization disciplined, cost-effective, and contractually sound. Principal Duties & Responsibilities: Vendor Governance & Performance Management Own the vendor governance framework for all infrastructure technology vendors and service providers Track and report on vendor SLA/KPI compliance across BPO, telecom, hardware, software, and cloud vendors Lead vendor performance reviews (QBRs, MBRs) and escalate performance gaps to the VP and relevant directors Maintain a vendor risk register and flag concentration risks, single-vendor dependencies, and end-of-life exposures Evaluate vendor roadmaps and alignment with Family Dollar's technology strategy Serve as an independent governance bridge between engineering teams and BPO partners - not embedded in either FinOps & Cost Optimization (Cloud + On-Premises) Lead FinOps practice across Azure, GCP, OCI, and on-premises infrastructure Own cost visibility dashboards, chargeback/showback models, and monthly spend reporting for the VP Identify and drive cost optimization opportunities: reserved instances, rightsizing, idle resource elimination, and license rationalization Define and enforce cloud cost governance policies in partnership with engineering teams Monitor cloud spend anomalies and alert leadership to budget variances in real time Maintain multi-year infrastructure cost forecasts and support annual budgeting cycles Partner with Finance to align infrastructure spend to business unit cost allocations Asset Management & Lifecycle Governance Own the end-to-end IT asset lifecycle governance process: procurement, deployment, tracking, and decommission Ensure CMDB accuracy and completeness as the authoritative system of record for all infrastructure assets Maintain hardware refresh schedules and lifecycle dashboards across stores, DCs, data centers, and cloud Partner with engineering teams to identify EoL/EoS risks and drive proactive refresh planning Govern software license entitlements and utilization to prevent compliance exposure Validate BPO asset inventory reporting and reconcile against procurement records Track and report on asset financial depreciation schedules in partnership with Finance Contract Management & Procurement Governance Own and manage all infrastructure technology contracts: renewal calendars, terms, SLAs, and obligations Lead contract renewals, amendments, and renegotiations in partnership with Legal, Procurement, and Finance Maintain a centralized contract repository with renewal triggers, expiration tracking, and risk flags Evaluate vendor proposals and new contracts to ensure alignment with technical and financial requirements Identify contract optimization opportunities: consolidation, renegotiation, and elimination of redundant agreements Enforce contract SLA commitments and hold vendors accountable through structured performance reviews Support RFP / RFI processes for infrastructure technology procurements Executive Reporting & Governance Intelligence Produce monthly and quarterly infrastructure governance dashboards for the VP, covering: vendor health, cost posture, asset lifecycle status, and contract obligations Maintain a unified governance scorecard across all infrastructure domains Prepare executive briefings, board-level summaries, and business case materials as needed Identify and escalate emerging governance risks: compliance gaps, cost overruns, vendor failures, and contractual exposure Develop and maintain governance policies, standards, and procedures for vendor, asset, and contract management BPO Oversight & Accountability Independently validate BPO performance against contracted SLAs and KPIs - separate from engineering directors Audit BPO invoices against contracted rates and service delivery Maintain a BPO performance scorecard and present findings to the VP on a regular cadence Identify BPO delivery gaps and work with the VP to initiate corrective action plans Track BPO-driven cost savings and efficiency commitments against actuals Security & Compliance Governance Support Maintain a mapping of infrastructure assets and vendors to regulatory and compliance frameworks (PCI-DSS, SOX) Track patch compliance and remediation SLAs across managed infrastructure domains Support audit readiness by maintaining governance documentation, contract evidence, and asset records Flag vendor or asset lifecycle risks that create compliance exposure Position Requirements Technical Knowledge Solid understanding of cloud platforms (Azure, GCP, OCI) and hybrid cloud cost structures Familiarity with enterprise infrastructure domains: networking, compute, storage, backup, and cloud Working knowledge of CMDB tooling (ServiceNow or equivalent) and asset lifecycle processes Understanding of software licensing models (perpetual, subscription, consumption-based) Proficiency with FinOps tooling and cloud cost management platforms (e.g., Apptio, CloudHealth, native cloud billing) Governance & Commercial Skills Proven expertise in contract lifecycle management: negotiation, renewal, compliance enforcement Experience building and executing vendor governance frameworks including SLA tracking and QBRs FinOps practitioner experience: chargeback, showback, reserved instance strategy, rightsizing Ability to develop executive-ready dashboards, governance reports, and financial models Strong analytical skills - able to synthesize complex data into actionable insights Familiarity with IT procurement and sourcing best practices Minimum Requirements: Education & Experience Bachelor's degree in Business, Information Technology, Finance, or a related field 8+ years of experience in IT governance, vendor management, FinOps, or IT asset management - within a large enterprise environment 3+ years in a role with direct accountability for technology contracts, vendor performance, or infrastructure cost management Experience operating in a multi-vendor, BPO-partnered IT delivery model Exposure to large-scale retail or distributed enterprise environments strongly preferred Preferred Qualifications: FinOps Certified Practitioner (FinOps Foundation) ITIL v4 Certification - Asset Management or Service Management tracks Certified Technology Procurement Professional (CTPP) or equivalent IAITAM Certified Asset Manager (ICAMP or CHAMP) Experience with ServiceNow ITAM/SAM, Flexera, or Snow Software Prior experience at a large-format retailer (Dollar General, Walmart, Target, etc.) Exposure to TSA (Transition Service Agreement) governance environments "Projected Salary Range: $120,000 - $135,000". Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and makes 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 IT Security Family Dollar

Job Title: Senior Databricks Engineer Location: Plano, TX Duration: Contract - 12 months Pay Range: $73.67/hr (W2) Job ID: 411755 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 Senior Databricks Engineer to join our dynamic team. The ideal candidate will have strong experience in Databricks Lakehouse Platform, Delta Lake, Unity Catalog, Delta Sharing, and CI/CD and a proven ability to design, optimize, govern, and migrate enterprise data solutions from Oracle to Databricks. Responsibilities: Design and implement scalable data solutions on the Databricks Lakehouse Platform. Partner with Application Leads and Engineering teams to define implementation approaches and best practices. Optimize Databricks environments for performance, scalability, reliability, and cost efficiency. Implement and support Unity Catalog, data governance, lineage, and security controls including RBAC. Design and manage data access controls and enable Delta Sharing for secure data exchange. Support Oracle-to-Databricks modernization and migration initiatives. Establish and enhance CI/CD processes, deployment automation, and DevOps best practices. Design, build, and manage semantic data models and business layers for Databricks SQL, AI/BI Dashboards, Genie, Power BI, and enterprise analytics. Develop standards, reusable patterns, and implementation guidance for application teams. Required Skills & Qualifications: 5+ years of Data Engineering experience. 3+ years of hands-on Databricks implementation experience. Strong knowledge of Databricks Lakehouse Platform, Delta Lake, Unity Catalog, and Delta Sharing. Experience implementing RBAC, security, governance, and data lineage solutions. Proven experience with Databricks performance tuning and cost optimization. Experience implementing CI/CD pipelines using Git, Azure DevOps, GitHub, Jenkins, or similar tools. Experience with cloud data platforms on Azure, AWS, or GCP. Strong understanding of data warehousing concepts and modern data architectures. Excellent communication and stakeholder collaboration skills. Experience level: 7+ years overall. Role type: Individual Contributor / Technical SME. Preferred Skills: Experience with Oracle to Databricks migration and modernization programs. Familiarity with Informatica PowerCenter and/or Informatica IDMC. Experience with Databricks Genie, AI/BI Dashboards, and Databricks SQL. Integration experience with Power BI. Knowledge of Databricks Workflows, Auto Loader, Delta Live Tables (DLT), Lakeflow, and MLflow. Experience with Infrastructure as Code tools such as Terraform. Databricks certifications. 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.

Job Description Job Description Provide a short description of the Position: The agency has a number of clinics, hospitals and outpatient facilities. The candidate will be responsible for managing projects related to updating and/or implementing new systems, software, and hardware. Provide a list of the day-to-day tasks to be performed by the Selected Candidate: Daily Tasks include but not limited to the following: Use project management tools, such as Microsoft Word, Excel, Project and Visio to allocate assignments, track project status and determine time estimates. Use project management methodology and documentation to manage the project. Plan and facilitiate all required project and technical meetings including demonstrations of application development progress. Provide regular status reports detailing project metrics, progress, and mitigation strategies underway to address concerns. Partner with Business Analyst to ensure the business requirements are elicited from Business owners and key stakeholders. Ensure requirements are communicated, documented, addressed and if approved, included in future project plans. Coordinate the development of test plans and testing with the Project Technical Lead. Act as facilitator and primary project manager for multiple projects related to the OMH Business efforts; including projects related to implementation of applications or infrastructure changes. Report status of current tasks and outstanding issues to supervisor. Adherre to all NYS Project Management directives and processes. Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of - Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.

DivIHN (pronounced "divine") is a CMMI ML3-certified Technology and Talent solutions firm. Driven by a unique Purpose, Culture, and Value Delivery Model, we enable meaningful connections between talented professionals and forward-thinking organizations. Since our formation in 2002, organizations across commercial and public sectors have been trusting us to help build their teams with exceptional temporary and permanent talent. Visit us at to learn more and view our open positions. Please apply or call one of us to learn more For further inquiries regarding the following opportunity, please contact our Talent Specialist, Deepak at or Dinesh at Title: AI Developer Location: Palo Alto, CA Duration: 3 Months Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered. Job Description: About the Team The Enterprise AI team is our client's internal AI enablement engine. They evaluate where AI can make a real difference, build the platforms and patterns that make adoption easy, and help engineering teams across the organization work smarter and faster. They operate at the intersection of applied AI, distributed systems, and enterprise operations their job is to make Client more efficient, one AI-powered workflow at a time. This is a high-impact, high-autonomy team where you'll work closely with engineering, product, and operations teams across our client to bring AI capabilities to life. About the Role As an Applied AI Developer on the Enterprise AI team, you'll evaluate where AI fits, build the tools and platforms that make it practical, and enable teams across our client to adopt modern AI development patterns including LLM orchestration, agentic workflows, and model governance. You stay hands-on and outcomes-oriented: prototyping, evaluating emerging AI technologies, and shipping solutions that make the organization measurably more efficient. What You'll Do Think AI-first assess where agentic approaches genuinely outperform conventional solutions, then own the quality bar: build automated evals, simulation tests, and regression frameworks that keep our AI systems reliable and improving as they scale. Design agentic systems tool orchestration, agent reasoning, memory, MCP integrations, and human-in-the-loop workflows. Define and implement AI governance patterns guardrails, data lineage, auditability, and responsible AI practices that ensure our agentic systems are safe, compliant, and trustworthy. Drive adoption through pilots, proofs-of-concept, and scalable implementations across engineering teams. Collaborate with various business functions, product, security, and platform teams to translate AI use cases into production-grade, end-to-end solutions. What We're Looking For 5+ years of professional software engineering, with at least 2 years focused on applied AI in production systems. Proficient in Python and/or Go; comfortable reading and writing in the other. Proven experience building and scaling multi-agent or agent-driven systems in production real-world operational ownership, not just simple LLM workflows. Hands-on experience with modern agent ecosystems, including frameworks (e.g., LangGraph, Google ADK, Mastra, Claude Agent SDK), observability and evals tooling (e.g., Langfuse, LangSmith, Braintrust), MCP implementations, and leading AI SDKs (e.g., OpenAI, Anthropic). Strong systems and backend architecture fundamentals designing scalable, reliable systems and handling infrastructure, performance, failure modes, cost, and deployment concerns. Good understanding of cloud-native environments (GCP and/or AWS) compute, storage, networking, and managed AI services. Experience designing and integrating with enterprise APIs (REST, GraphQL) including authentication and authorization patterns (OAuth2, SAML, API keys, RBAC). Comfortable working with backend databases (SQL and NoSQL) writing queries, understanding data models, and building data access layers that enforce role-based access control. Strong cross-functional collaborator and communicator, able to partner with Product, Operations, and domain experts to deliver end-to-end systems with measurable real-world impact. A force-multiplier on the team you raise the bar for clarity of thinking, system design standards, and team execution. Nice to Have Experience with AI evaluation tooling (Langfuse, LangSmith, Braintrust, or custom eval frameworks). Experience building custom MCP servers, not just consuming them. Familiarity with containerization and orchestration (Docker, Kubernetes). AI-native builder with high velocity and ownership intellectual curiosity, rapid adoption of new tools, bias to action, and the ability to drive ambiguous problems from concept to production. Hands-on experience with inference cost optimization managing spend as agent deployments scale. Experience using AI-powered coding agents (e.g., Claude Code, GitHub Copilot, Cursor, Windsurf) to accelerate development workflows rapid prototyping, code generation, debugging, and test writing. Experience with RAG (Retrieval-Augmented Generation) architectures and document retrieval pipelines vector databases, embedding models, chunking strategies, and hybrid search for building agents that answer questions grounded in enterprise documentation. About us: DivIHN, the 'IT Asset Performance Services' organization, provides Professional Consulting, Custom Projects, and Professional Resource Augmentation services to clients in the Mid-West and beyond. The strategic characteristics of the organization are Standardization, Specialization, and Collaboration. DivIHN is an equal opportunity employer. DivIHN does not and shall not discriminate against any employee or qualified applicant on the basis of race, color, religion (creed), gender, gender expression, age, national origin (ancestry), disability, marital status, sexual orientation, or military status.

Job Title: AWS Cloud Infrastructure Engineer Location: Jersey City, NJ Duration: Contract - 6 months Pay Range: $75/hr - $85/hr (W2) 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. We are seeking an experienced AWS Cloud Infrastructure Engineer to design and deliver scalable, secure, and resilient cloud infrastructure solutions. This role focuses on AWS networking, compute, storage, and infrastructure automation. The ideal candidate will have strong AWS expertise, experience with Terraform, and the ability to partner with application teams to understand requirements and develop effective technical solutions. Responsibilities Design and deliver AWS infrastructure solutions across networking, compute, storage, and EC2. Partner with application teams across the organization to understand business requirements and architect appropriate infrastructure solutions. Build, maintain, and deliver reusable Terraform modules consumed by application teams. Support cloud infrastructure initiatives across a large, enterprise-scale environment. Establish and maintain CI/CD pipelines and infrastructure delivery practices. Collaborate with engineering teams to develop scalable, reliable, and secure cloud solutions. Evaluate technical requirements, recommend appropriate solutions, and contribute to infrastructure architecture decisions. Support continuous improvement of cloud infrastructure capabilities, automation, and engineering practices. Required Skills & Qualifications Strong hands-on AWS experience across networking, compute, and storage. Candidates may have deeper expertise in one or more areas. Experience with AWS infrastructure services, including EC2. Experience building and delivering Terraform modules or reusable infrastructure-as-code solutions. Familiarity with CI/CD pipelines and automated infrastructure delivery. Experience with GitHub and/or Bitbucket. Strong technical problem-solving and solutioning skills. Ability to collaborate with application teams and translate requirements into infrastructure solutions. Ability to work effectively in a large enterprise environment and quickly contribute to ongoing engineering initiatives. Approximately 5-7+ years of relevant experience. Preferred Skills Experience with Google Cloud Platform (GCP). Experience with Go (Golang). Python experience, particularly for developing or supporting AWS Lambda functions. Java development experience, particularly for candidates with strong AWS infrastructure expertise. Experience working across multiple engineering teams to design and implement cloud infrastructure 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.

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