Distinguished AI Engineer (Remote) Job Description 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 8 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 6 years of experience developing AI and ML algorithms or technologies - At least 8 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: - 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) - Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems - Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level - 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 At this time, Capital One will not sponsor a new 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. Remote (Regardless of Location): $244,700 - $279,200 for Distinguished AI Engineer McLean, VA: $269,100 - $307,200 for Distinguished 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 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com 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).

Role Description We are looking for a Salesforce AI Integration Architect to design and build enterprise integrations between internal AI platforms, enterprise systems, and Salesforce Agentforce environments, enabling autonomous AI workflows at scale. You will architect distributed systems and multi-step agentic AI orchestration patterns, develop Salesforce-native integrations, and establish governance, security, and trust frameworks for AI-enabled enterprise solutions. The role requires deep expertise in Salesforce customization, AI/LLM orchestration, enterprise integrations, and scalable distributed system design. What You Will Do - Architect end-to-end integrations between internal AI platforms, enterprise data systems, and Salesforce Agentforce environments; - Design scalable, secure, and resilient distributed system architectures supporting autonomous AI workflows; - Design and optimize modular agentic AI systems, avoiding monolithic reasoning architectures through specialized micro-agent delegation; - Build orchestration patterns for multi-step AI workflows, autonomous routing systems, and semantic tool execution; - Apply best practices around Prompt Engineering, Context Management, Token Conservation, and LLM Orchestration; - Develop and enhance integrations using Salesforce Flows, Invocable Apex Methods, APIs, connectors, and custom prompt templates; - Enable complex backend processes to be exposed as intelligent agentic tools within Salesforce ecosystems; - Collaborate with cross-functional teams to maintain unified API contracts and semantic consistency across enterprise systems; - Author comprehensive Architectural Decision Records (ADRs) documenting technical trade-offs, constraints, and High-Level Requirements (HLRs); - Evaluate and select optimal integration patterns including Traditional APIs, Model Context Protocol (MCP), and Agent-to-Agent (A2A) communication models; - Balance performance, latency, scalability, reasoning overhead, and data sensitivity considerations in architectural decisions; - Establish authentication boundaries, trust layers, and governance guardrails for AI-enabled enterprise systems; - Ensure compliance with enterprise security standards, data governance policies, and secure data exposure practices; - Partner with security and platform teams to maintain reliable and trustworthy autonomous agent execution. Qualifications - 6+ years of experience designing enterprise integrations and distributed system architectures; - Hands-on experience integrating systems with Salesforce; - Deep expertise with Apex Methods, Advanced Salesforce Flows, Custom Prompt Templates, Salesforce APIs, and connectors; - Strong experience with REST APIs; - Solid understanding of AI/LLM concepts including Prompt Engineering, Context Management, Token Optimization, Multi-step AI Workflows, Agent Orchestration, and Semantic Routing Systems; - Experience designing scalable and secure distributed systems; - Strong understanding of authentication, security, trust boundaries, and data governance; - Experience documenting architecture decisions, trade-offs, and technical strategy; - Excellent collaboration and communication skills across engineering, platform, data, and security organizations; - Upper-intermediate English level. Nice to Haves - Experience with gRPC; - Experience with Event-Driven Architectures; - Experience with enterprise synchronization patterns; - Experience with Model Context Protocol (MCP); - Experience with Agent-to-Agent (A2A) integrations; - Experience with MuleSoft or enterprise middleware platforms; - Familiarity with Salesforce Agentforce; - Experience building or managing autonomous AI agents or micro-agent ecosystems; - Experience with semantic tool discovery or AI-native integrations; - Knowledge of Salesforce Bulk APIs and Salesforce Connect; - Experience operating within large-scale enterprise AI environments. Benefits - Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps. - Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation. - Exciting projects: Join projects with modern solutions development and top-tier clients, including Fortune 500 enterprises and leading product brands. - Flextime: Tailor your schedule for an optimal work-life balance, with options for remote work and flexible hours.

• Design, build, and maintain integrations between the Anthropic Claude platform and enterprise systems • Develop and manage MCP server configurations • Build and optimize prompt pipelines, agentic workflows, and automations • Troubleshoot complex technical issues across the AI stack • Write clean, well-documented code • Test and iterate on AI workflows

Role Description We’re looking for a senior individual contributor who can independently lead delivery of an LLM feature area, including eval strategy and production readiness. As a Senior AI Engineer (GenAI), you’ll: - Build end-to-end LLM applications, from prototyping prompts and agentic workflows to production-grade services with evaluation, monitoring, and iteration loops. - Work on agent orchestration (e.g., Lang Chain/Lang Graph-style patterns) and establish LLM evaluation frameworks. - Build and ship LLM-powered product capabilities end-to-end: APIs, orchestration logic, integrations, and production rollouts. - Design and implement agentic workflows using modern orchestration frameworks (e.g., LangChain / LangGraph-style). - Develop strong prompting and context engineering practices, including prompt versioning and experimentation. - Build evaluation harnesses for LLM apps: curated test sets, scenario-based evals, automated checks, offline/online quality metrics, human review loops, regression gates, and release criteria for model/prompt/workflow changes. - Implement safety and reliability patterns for LLM systems, including guardrails, tool permissions, prompt-injection awareness, fallback handling, and secure data handling. - Own production readiness for AI features, including rollout plans, monitoring, incident response inputs, performance tuning, and post-launch iteration. - Experience designing clean API/tool interfaces for LLM workflows, including structured inputs/outputs, schema validation, error handling, retries, and observability. - Collaborate with platform/infra teams to deploy on AWS or GCP, ensuring reliability, scalability, latency, and cost controls. - Instrument systems for observability (quality, latency, token/cost, errors) and create feedback loops to improve model and system behavior over time. - Work cross-functionally with Product/Design to translate ambiguous problems into measurable outcomes and shippable iterations. - Use AI-assisted development tools responsibly to accelerate coding, testing, debugging, documentation, and experimentation while maintaining strong engineering standards for review, quality, security, and maintainability. Qualifications - 5-8 years of professional experience in software engineering, applied ML, data science engineering, or AI product engineering. - Strong Python skills, and experience building backend services (e.g., Flask/FastAPI) and integrating with REST APIs. - Practical understanding of LLMs/SLMs and how they behave in production (hallucinations, prompt sensitivity, latency/cost tradeoffs). - Hands-on experience building LLM applications (RAG, tool use, agents, workflow orchestration), with the ability to demonstrate end-to-end ownership from prototype → production → measurement → iteration. - Awareness of production AI risks such as hallucinations, prompt injection, unsafe tool use, data leakage, privacy concerns, and model/output drift. - Experience with cloud infrastructure (AWS or GCP) and shipping production workloads (containers, deployments, monitoring). - Strong engineering fundamentals: testing, debugging, performance thinking, and clean, maintainable design. - Excellent communication skills and ability to collaborate effectively in fast-paced, agile environments. - Practical experience using AI-assisted engineering tools such as Cursor, GitHub Copilot, Claude, ChatGPT, or similar tools to improve developer productivity without compromising code quality. Requirements - Experience with LLM evaluation/observability tooling (e.g., experiment tracking, tracing, prompt/version management, continuous evaluation). - Familiarity with vector databases / retrieval systems and relevance tuning (RAG patterns, embedding selection, chunking strategies). - Prior work on agent reliability patterns: guardrails, tool error handling, fallbacks, and human-in-the-loop designs. - Experience with CI/CD, Docker/Kubernetes, or infrastructure-as-code. - Bachelor’s degree in computer science, Engineering, or equivalent practical experience is preferred. Benefits - Purpose led company with a Values focused culture – Best Life, One Team, Growth Mindset. - Time Off – with our open PTO policy, you pick when you want time off when it’s best for you! - Days of Disconnect – once a quarter, we take a collective breather and enjoy a day off together around the globe. - Parental & Pawternity Leave – we offer leave for when your family grows by two feet or four paws! - Fitness Perk – we are committed to meeting you wherever you are in your fitness journey with a quarterly reimbursement. - Discounts – access to discounts with our partners, such as Dell, Microsoft & many more. - Medical/Dental/Vision coverage. - EAP – we get you help when you need it. Period. - Calm App +4 – enjoy tranquility with a Calm App subscription for you and up to 4 dependents over the age of 16. - And more! – so many benefits we couldn’t even fit them all here!