Job Description Job Description Dark Wolf Solutions is seeking Security Control Assessor/Representatives (SCA/Rs) to lead security control assessments across high-priority projects. Working at the intersection of cybersecurity engineering, cloud architecture, and DevSecOps prototyping, you will evaluate security controls for cutting-edge AI/LLM technologies across multiple classification levels. This position is ideal for a pragmatic cloud assessor or SCAR who excels in fast-paced DevSecOps environments, understands AWS cloud security, and is eager to shape the cybersecurity posture of next-generation DoD AI capabilities.This position will be based out of Arlington, VA. Additional responsibilities include: Key Responsibilities Execute formal SCA/R duties. Lead security assessment efforts, establishing reusable security playbooks and assessment frameworks for rapid AI deployment into enterprise workflows. Evaluate technical control effectiveness across AWS cloud infrastructure, DevSecOps pipelines, microservices, containerized workloads, and GenAI/LLM application stacks. Partner directly with cybersecurity engineering and DevSecOps prototyping teams to integrate security controls early in the development lifecycle. Review, author, and maintain assessment packages-including System Security Plans (SSPs), Security Assessment Plans (SAPs), Security Assessment Reports (SARs), and POA&Ms-tailored to rapid prototyping and AI systems. Assess technical security risks specific to AI/LLM implementations, such as API exposure, vector database access controls, model integration surface area, and software supply chain dependencies. Support continuous monitoring (ConMon), technical risk evaluations, and cloud architecture reviews across multi-tenant, multi-classification environments. Coordinate with Authorizing Officials (AOs), program managers, and engineering leads to deliver decision-ready risk briefings and ATO recommendations. Provide technical input and oversight for cybersecurity engineering and penetration testing activities across prototype projects. Required Qualifications Active Top Secret security clearance Current DoD 8570/8140 IAM Level II or Level III certification (e.g., Security+, CySA+, CISM, CISSP, CCISO, CAP/CISC) 3-5+ years of experience conducting security control assessments, compliance testing, or A&A/RMF activities for DoD or federal information systems Solid operational understanding of core AWS cloud services (EC2, S3, IAM, VPCs, Security Groups, Security Hub) and how security controls function within cloud-native and CI/CD pipeline environments. Strong working knowledge of NIST SP 800-53 (Rev. 4/5), NIST SP 800-37 (RMF), DoD Cloud Computing SRG, and FedRAMP baselines. Demonstrated experience writing and evaluating core RMF artifacts (SSPs, SAPs, SARs, POA&Ms) Exceptional written and verbal communication skills, with the ability to articulate technical risk clearly to executive stakeholders, Authorizing Officials, and engineering teams. Hands-on experience navigating government GRC repositories, such as eMASS or XACTA. Desired Qualifications Hands-on experience mapping security controls to the NIST AI Risk Management Framework (AI RMF), the OWASP Top 10 for LLM Applications, or the DoD Responsible AI (RAI) Guidelines. Familiarity evaluating secure design patterns for autonomous AI Agents (e.g., tool-calling permissions, sandboxing agent execution environments, prompt boundaries, and ReAct/LangGraph architectures). Experience assessing cloud-managed AI ecosystems and foundation model platforms (e.g., AWS Bedrock, AWS SageMaker, Hugging Face Enterprise, or self-hosted open-source models). Understanding of data protection, access controls, and boundary security for RAG pipelines and vector databases (e.g., OpenSearch Vector Engine, Pinecone, Milvus, or PostgreSQL pgvector). Familiarity evaluating risks unique to LLMs-including prompt injection, data poisoning, model inversion, insecure output handling, and open-source supply chain vulnerabilities in AI libraries (PyTorch, LangChain, LlamaIndex). Exposure to LLM guardrail platforms, evaluation frameworks, or AI security tools (e.g., Promptfoo, Garak, Giskard, NeMo Guardrails) used to test model robustness and output safety. Experience with cATO methodologies, Infrastructure as Code (IaC) templates (Terraform, CloudFormation), and container security (AWS EKS/ECS, Docker). Active AWS Certifications (e.g., AWS Certified Security - Specialty or AWS Certified Solutions Architect). Background or familiarity with offensive security, penetration testing The salary range for this position is estimated to be between $135,000.00 - $150,000.00, commensurate on experience and technical skillset. We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories. In compliance with federal law, all persons hired will be required to verify identity, confirm US Citizenship, and complete the required employment eligibility verification upon hire. We are strictly looking for direct, full-time W2 employees. We do not engage with third-party staffing agencies, C2C, or 1099 independent contractors for this role.
09/15/2026
Full time
Job Description Job Description Dark Wolf Solutions is seeking Security Control Assessor/Representatives (SCA/Rs) to lead security control assessments across high-priority projects. Working at the intersection of cybersecurity engineering, cloud architecture, and DevSecOps prototyping, you will evaluate security controls for cutting-edge AI/LLM technologies across multiple classification levels. This position is ideal for a pragmatic cloud assessor or SCAR who excels in fast-paced DevSecOps environments, understands AWS cloud security, and is eager to shape the cybersecurity posture of next-generation DoD AI capabilities.This position will be based out of Arlington, VA. Additional responsibilities include: Key Responsibilities Execute formal SCA/R duties. Lead security assessment efforts, establishing reusable security playbooks and assessment frameworks for rapid AI deployment into enterprise workflows. Evaluate technical control effectiveness across AWS cloud infrastructure, DevSecOps pipelines, microservices, containerized workloads, and GenAI/LLM application stacks. Partner directly with cybersecurity engineering and DevSecOps prototyping teams to integrate security controls early in the development lifecycle. Review, author, and maintain assessment packages-including System Security Plans (SSPs), Security Assessment Plans (SAPs), Security Assessment Reports (SARs), and POA&Ms-tailored to rapid prototyping and AI systems. Assess technical security risks specific to AI/LLM implementations, such as API exposure, vector database access controls, model integration surface area, and software supply chain dependencies. Support continuous monitoring (ConMon), technical risk evaluations, and cloud architecture reviews across multi-tenant, multi-classification environments. Coordinate with Authorizing Officials (AOs), program managers, and engineering leads to deliver decision-ready risk briefings and ATO recommendations. Provide technical input and oversight for cybersecurity engineering and penetration testing activities across prototype projects. Required Qualifications Active Top Secret security clearance Current DoD 8570/8140 IAM Level II or Level III certification (e.g., Security+, CySA+, CISM, CISSP, CCISO, CAP/CISC) 3-5+ years of experience conducting security control assessments, compliance testing, or A&A/RMF activities for DoD or federal information systems Solid operational understanding of core AWS cloud services (EC2, S3, IAM, VPCs, Security Groups, Security Hub) and how security controls function within cloud-native and CI/CD pipeline environments. Strong working knowledge of NIST SP 800-53 (Rev. 4/5), NIST SP 800-37 (RMF), DoD Cloud Computing SRG, and FedRAMP baselines. Demonstrated experience writing and evaluating core RMF artifacts (SSPs, SAPs, SARs, POA&Ms) Exceptional written and verbal communication skills, with the ability to articulate technical risk clearly to executive stakeholders, Authorizing Officials, and engineering teams. Hands-on experience navigating government GRC repositories, such as eMASS or XACTA. Desired Qualifications Hands-on experience mapping security controls to the NIST AI Risk Management Framework (AI RMF), the OWASP Top 10 for LLM Applications, or the DoD Responsible AI (RAI) Guidelines. Familiarity evaluating secure design patterns for autonomous AI Agents (e.g., tool-calling permissions, sandboxing agent execution environments, prompt boundaries, and ReAct/LangGraph architectures). Experience assessing cloud-managed AI ecosystems and foundation model platforms (e.g., AWS Bedrock, AWS SageMaker, Hugging Face Enterprise, or self-hosted open-source models). Understanding of data protection, access controls, and boundary security for RAG pipelines and vector databases (e.g., OpenSearch Vector Engine, Pinecone, Milvus, or PostgreSQL pgvector). Familiarity evaluating risks unique to LLMs-including prompt injection, data poisoning, model inversion, insecure output handling, and open-source supply chain vulnerabilities in AI libraries (PyTorch, LangChain, LlamaIndex). Exposure to LLM guardrail platforms, evaluation frameworks, or AI security tools (e.g., Promptfoo, Garak, Giskard, NeMo Guardrails) used to test model robustness and output safety. Experience with cATO methodologies, Infrastructure as Code (IaC) templates (Terraform, CloudFormation), and container security (AWS EKS/ECS, Docker). Active AWS Certifications (e.g., AWS Certified Security - Specialty or AWS Certified Solutions Architect). Background or familiarity with offensive security, penetration testing The salary range for this position is estimated to be between $135,000.00 - $150,000.00, commensurate on experience and technical skillset. We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories. In compliance with federal law, all persons hired will be required to verify identity, confirm US Citizenship, and complete the required employment eligibility verification upon hire. We are strictly looking for direct, full-time W2 employees. We do not engage with third-party staffing agencies, C2C, or 1099 independent contractors for this role.
Job Description Job Description Dark Wolf Solutions is seeking Security Control Assessor/Representatives (SCA/Rs) to lead security control assessments across high-priority projects. Working at the intersection of cybersecurity engineering, cloud architecture, and DevSecOps prototyping, you will evaluate security controls for cutting-edge AI/LLM technologies across multiple classification levels. This position is ideal for a pragmatic cloud assessor or SCAR who excels in fast-paced DevSecOps environments, understands AWS cloud security, and is eager to shape the cybersecurity posture of next-generation DoD AI capabilities.This position will be based out of Arlington, VA with hybrid/remote opportunities. Additional responsibilities include: Key Responsibilities Execute formal SCA/R duties. Lead security assessment efforts, establishing reusable security playbooks and assessment frameworks for rapid AI deployment into enterprise workflows. Evaluate technical control effectiveness across AWS cloud infrastructure, DevSecOps pipelines, microservices, containerized workloads, and GenAI/LLM application stacks. Bridge the gap between OffSec and development by applying software design best practices. Lead technical exchange meetings (TEMs), participate in Discovery & Framing workshops, and maintain effective communication with cross-functional teams and stakeholders. Act as the primary subject matter expert and lead developer for custom offensive tooling, integrating disparate capabilities into a cohesive, mission-ready platform. Review, author, and maintain assessment packages-including System Security Plans (SSPs), Security Assessment Plans (SAPs), Security Assessment Reports (SARs), and POA&Ms-tailored to rapid prototyping and AI systems. Assess technical security risks specific to AI/LLM implementations, such as API exposure, vector database access controls, model integration surface area, and software supply chain dependencies. Support continuous monitoring (ConMon), technical risk evaluations, and cloud architecture reviews across multi-tenant, multi-classification environments. Coordinate with Authorizing Officials (AOs), program managers, and engineering leads to deliver decision-ready risk briefings and ATO recommendations. Provide technical input and oversight for cybersecurity engineering and penetration testing activities across prototype projects. Required Qualifications Active Top Secret security clearance Current DoD 8570/8140 IAM Level II or Level III certification (e.g., Security+, CySA+, CISM, CISSP, CCISO, CAP/CISC) 5-7+ years of experience conducting security control assessments, compliance testing, or A&A/RMF activities for DoD or federal information systems Solid operational understanding of core AWS cloud services (EC2, S3, IAM, VPCs, Security Groups, Security Hub) and how security controls function within cloud-native and CI/CD pipeline environments. Experience with GitLab CI/CD (pipeline design, runners, artifact management) and AWS Cloud services (EC2, VPC, IAM, S3). Strong working knowledge of NIST SP 800-53 (Rev. 4/5), NIST SP 800-37 (RMF), DoD Cloud Computing SRG, and FedRAMP baselines. Demonstrated experience writing and evaluating core RMF artifacts (SSPs, SAPs, SARs, POA&Ms) Exceptional written and verbal communication skills, with the ability to articulate technical risk clearly to executive stakeholders, Authorizing Officials, and engineering teams. Hands-on experience navigating government GRC repositories, such as eMASS or XACTA. Desired Qualifications Hands-on experience mapping security controls to the NIST AI Risk Management Framework (AI RMF), the OWASP Top 10 for LLM Applications, or the DoD Responsible AI (RAI) Guidelines. Familiarity evaluating secure design patterns for autonomous AI Agents (e.g., tool-calling permissions, sandboxing agent execution environments, prompt boundaries, and ReAct/LangGraph architectures). Experience assessing cloud-managed AI ecosystems and foundation model platforms (e.g., AWS Bedrock, AWS SageMaker, Hugging Face Enterprise, or self-hosted open-source models). Understanding of data protection, access controls, and boundary security for RAG pipelines and vector databases (e.g., OpenSearch Vector Engine, Pinecone, Milvus, or PostgreSQL pgvector). Familiarity evaluating risks unique to LLMs-including prompt injection, data poisoning, model inversion, insecure output handling, and open-source supply chain vulnerabilities in AI libraries (PyTorch, LangChain, LlamaIndex). Exposure to LLM guardrail platforms, evaluation frameworks, or AI security tools (e.g., Promptfoo, Garak, Giskard, NeMo Guardrails) used to test model robustness and output safety. Experience with cATO methodologies, Infrastructure as Code (IaC) templates (Terraform, CloudFormation), and container security (AWS EKS/ECS, Docker). Active AWS Certifications (e.g., AWS Certified Security - Specialty or AWS Certified Solutions Architect). Background or familiarity with offensive security, penetration testing The salary range for this position is estimated to be between $135,000.00 - $160,000.00, commensurate on experience and technical skillset. We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories. In compliance with federal law, all persons hired will be required to verify identity, confirm US Citizenship, and complete the required employment eligibility verification upon hire. We are strictly looking for direct, full-time W2 employees. We do not engage with third-party staffing agencies, C2C, or 1099 independent contractors for this role.
09/15/2026
Full time
Job Description Job Description Dark Wolf Solutions is seeking Security Control Assessor/Representatives (SCA/Rs) to lead security control assessments across high-priority projects. Working at the intersection of cybersecurity engineering, cloud architecture, and DevSecOps prototyping, you will evaluate security controls for cutting-edge AI/LLM technologies across multiple classification levels. This position is ideal for a pragmatic cloud assessor or SCAR who excels in fast-paced DevSecOps environments, understands AWS cloud security, and is eager to shape the cybersecurity posture of next-generation DoD AI capabilities.This position will be based out of Arlington, VA with hybrid/remote opportunities. Additional responsibilities include: Key Responsibilities Execute formal SCA/R duties. Lead security assessment efforts, establishing reusable security playbooks and assessment frameworks for rapid AI deployment into enterprise workflows. Evaluate technical control effectiveness across AWS cloud infrastructure, DevSecOps pipelines, microservices, containerized workloads, and GenAI/LLM application stacks. Bridge the gap between OffSec and development by applying software design best practices. Lead technical exchange meetings (TEMs), participate in Discovery & Framing workshops, and maintain effective communication with cross-functional teams and stakeholders. Act as the primary subject matter expert and lead developer for custom offensive tooling, integrating disparate capabilities into a cohesive, mission-ready platform. Review, author, and maintain assessment packages-including System Security Plans (SSPs), Security Assessment Plans (SAPs), Security Assessment Reports (SARs), and POA&Ms-tailored to rapid prototyping and AI systems. Assess technical security risks specific to AI/LLM implementations, such as API exposure, vector database access controls, model integration surface area, and software supply chain dependencies. Support continuous monitoring (ConMon), technical risk evaluations, and cloud architecture reviews across multi-tenant, multi-classification environments. Coordinate with Authorizing Officials (AOs), program managers, and engineering leads to deliver decision-ready risk briefings and ATO recommendations. Provide technical input and oversight for cybersecurity engineering and penetration testing activities across prototype projects. Required Qualifications Active Top Secret security clearance Current DoD 8570/8140 IAM Level II or Level III certification (e.g., Security+, CySA+, CISM, CISSP, CCISO, CAP/CISC) 5-7+ years of experience conducting security control assessments, compliance testing, or A&A/RMF activities for DoD or federal information systems Solid operational understanding of core AWS cloud services (EC2, S3, IAM, VPCs, Security Groups, Security Hub) and how security controls function within cloud-native and CI/CD pipeline environments. Experience with GitLab CI/CD (pipeline design, runners, artifact management) and AWS Cloud services (EC2, VPC, IAM, S3). Strong working knowledge of NIST SP 800-53 (Rev. 4/5), NIST SP 800-37 (RMF), DoD Cloud Computing SRG, and FedRAMP baselines. Demonstrated experience writing and evaluating core RMF artifacts (SSPs, SAPs, SARs, POA&Ms) Exceptional written and verbal communication skills, with the ability to articulate technical risk clearly to executive stakeholders, Authorizing Officials, and engineering teams. Hands-on experience navigating government GRC repositories, such as eMASS or XACTA. Desired Qualifications Hands-on experience mapping security controls to the NIST AI Risk Management Framework (AI RMF), the OWASP Top 10 for LLM Applications, or the DoD Responsible AI (RAI) Guidelines. Familiarity evaluating secure design patterns for autonomous AI Agents (e.g., tool-calling permissions, sandboxing agent execution environments, prompt boundaries, and ReAct/LangGraph architectures). Experience assessing cloud-managed AI ecosystems and foundation model platforms (e.g., AWS Bedrock, AWS SageMaker, Hugging Face Enterprise, or self-hosted open-source models). Understanding of data protection, access controls, and boundary security for RAG pipelines and vector databases (e.g., OpenSearch Vector Engine, Pinecone, Milvus, or PostgreSQL pgvector). Familiarity evaluating risks unique to LLMs-including prompt injection, data poisoning, model inversion, insecure output handling, and open-source supply chain vulnerabilities in AI libraries (PyTorch, LangChain, LlamaIndex). Exposure to LLM guardrail platforms, evaluation frameworks, or AI security tools (e.g., Promptfoo, Garak, Giskard, NeMo Guardrails) used to test model robustness and output safety. Experience with cATO methodologies, Infrastructure as Code (IaC) templates (Terraform, CloudFormation), and container security (AWS EKS/ECS, Docker). Active AWS Certifications (e.g., AWS Certified Security - Specialty or AWS Certified Solutions Architect). Background or familiarity with offensive security, penetration testing The salary range for this position is estimated to be between $135,000.00 - $160,000.00, commensurate on experience and technical skillset. We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories. In compliance with federal law, all persons hired will be required to verify identity, confirm US Citizenship, and complete the required employment eligibility verification upon hire. We are strictly looking for direct, full-time W2 employees. We do not engage with third-party staffing agencies, C2C, or 1099 independent contractors for this role.
Senior Lead AI Engineer (GenAI Platform Services) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 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).
09/14/2026
Full time
Senior Lead AI Engineer (GenAI Platform Services) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 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).