• Own a portfolio of 3–5 states; develop and maintain a territory capture plan for each state defining ICPs, political context, trigger conditions, relationship maps, assets in market, and 90-day activity plans • Develop state-specific win strategies that include identification of target opportunities, understanding of political and procurement context, and prioritized next actions • Translate market intelligence from the RevOps/BD Analyst layer into qualified leads and recommended actions tied to specific opportunities • Lead discovery sessions, technical workshops, and working sessions with state agency stakeholders; pull in Solutions Architects only where technical depth genuinely requires it • Conduct pre-RFP requirement shaping conversations with agency stakeholders to define procurement requirements that favor Nava’s approach • Build and maintain warm, trust-based relationships with 8–12 state agency contacts per territory, including economic buyers, technical evaluators, political blockers, and internal champions • Deliver value-additive touchpoints to stakeholders — peer state intelligence, federal guidance, relevant case studies — without explicit asks • Hold credible conversations with state CIOs and agency program directors on agency strategic priorities, federal compliance environment, technical architecture, and operational challenges without needing a lifeline • Represent Nava at relevant conferences, state-level events, and industry gatherings within assigned territories • Self-generate outbound materials including one-pagers, briefing packets, state-specific capability summaries, and demo assets using AI-native tools and Nava’s institutional knowledge base • Develop product-based wedge materials — prototypes, demonstration assets, and click-engagement content — that support the state product-led go-to-market motion • Operate with an AI-first orientation across intelligence gathering, asset creation, synthesis, and outbound strategy; use AI tools to reduce time on tasks that do not require human judgment • Own win theme development and pursuit strategy on below-threshold opportunities; co-lead with the Capture Manager on above-threshold pursuits • Surface opportunity signals into the pipeline — budget shifts, personnel changes, federal compliance pressure, peer state movements — each tied to a recommended next action • Coordinate with RevOps so intelligence flows bidirectionally, oriented to the territory capture plan • Identify when a POC or product demonstration is the right next move; design and lead those engagements with Solutions Architect depth pulled in as needed

• Embed with customers and own the outcome. Sit alongside customer teams — in their Slack, their systems, their reality — to understand their workflows, constraints, and data before touching a line of code. Translate what you hear into a concrete technical plan, then execute it. • Run technical discovery before every engagement. Map the customer’s existing stack: SAP configuration, CRM schema, data flows, integration points, and business rules. Ask the questions the customer didn’t know mattered. Define scope before scope defines you. • Build and deploy production solutions, not prototypes. Stand up integrations, data pipelines, custom workflows, and tenant configurations that run in live environments. “It works on my machine” is not a deliverable. • Own the full integration lifecycle. From first API call to stable sync: SAP/ERP data flows, CRM connections, customer-master and order-master mapping, idempotent event handling, and the edge cases that only appear in production with real data. • Be the primary technical relationship. Serve as the customer’s technical point of contact across the engagement — from onboarding through steady state. Run technical calls, explain architectural decisions to non-technical stakeholders, and surface risks before they become incidents. • Support sales in technically complex deals. Join pre-sales conversations to assess feasibility, design proof-of-concept scopes, and give prospective customers the confidence that Vailent can work in their environment. The close and the deployment aren’t separate jobs. • Direct AI agents through customer-specific work. Decompose integration and configuration tasks, fan them out to parallel agents, verify outputs adversarially, and reconcile results — without letting customer data or live-system risk become casualty of throughput. • Close the feedback loop with product and engineering. The patterns, failure modes, and workarounds you discover in the field are the most valuable signal the core team has. Document them, escalate them, and advocate for the generalized fix — not the one-off patch. • Capture and reuse what works. Build deployment runbooks, integration templates, customer onboarding checklists, and Claude skills that make the next engagement faster. Treat every repeated setup task as a bug to be fixed once and inherited forever. • Author the thinking, not just the code. Specs, discovery-question sets, integration design docs, and handoff notes that let the next engineer — or agent — pick up where you left off without a two-hour call.

Distinguished Engineer, Full Stack (Remote Eligible) As a Distinguished Engineer at Capital One, you will be a part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers, AI/ML experts, data analysts, product managers and people leaders. Our Distinguished Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while driving towards strong technology solutions. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence, and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring internal talent and actively recruiting to keep building our community. Distinguished Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other material to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization. In this role, you will work with our Capital Markets and Financial Planning Technology teams as well as the broader Finance Technology Distinguished Engineer community to drive architectural excellence, establish AI-native engineering standards, and deliver the next generation of liquidity management, predictive analytics and financial planning infrastructure that powers Capital One's most consequential financial decisions. If you are ready to provide thought leadership and build engineering excellence across Capital One's engineering teams, come join us in our mission to change banking for good. Key responsibilities: - Articulate and evangelize a bold technical vision for your domain - Decompose complex problems into practical and operational solutions - Ensure the quality of technical design and implementation - Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability - Continue learning and injecting advanced technical knowledge into our community - Handle several projects simultaneously, balancing your time to maximize impact - Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community - Lead proof-of-concept development for emerging AI frameworks and architectural patterns - Collaborate with other Finance Technology towers reviewing architectures and designs outside your immediate domain and contributing a cross-cutting perspective that raises the bar org-wide - Champion AIOps practices - driving platform reliability through AI-assisted anomaly detection, automated remediation, and predictive alerting across the portfolio Basic Qualifications: - Bachelor's Degree - At least 7 years of experience in the following: - Software engineering and solution architecture - Enterprise architecture and design patterns - Designing and building distributed HPC and ML systems - Full ML development lifecycle using AI and ML frameworks - Cloud computing (AWS, Microsoft Azure, Google Cloud) - Data engineering Preferred Qualifications: - Bachelor's or Master's in Computer Science, Applied Mathematics, or a related technical field - 10+ years of experience in one or more of: software engineering and solution architecture, enterprise architecture and design patterns, distributed HPC and ML systems, ML development lifecycle, cloud computing, or data architecture - 10+ years of hands-on coding in commonly used languages Python, Java, Go, Scala, JavaScript/TypeScript, or similar; you are a working engineer, not a former engineer - 8+ years owning the full SDLC , conception through architecture, implementation, testing, deployment, and production support; you have been paged and you have fixed it - Demonstrated AI-native engineering practice across all three layers: - Daily use of AI coding assistants to accelerate productivity, utilizing capabilities well beyond basic code completion - Spec/intent driven development - AI embedded in CI/CD and SDLC tooling - test generation, spec validation, code review augmentation - Production experience building LLM-backed or agentic systems - prompt engineering, evaluation frameworks, observability, and guardrails included - Experience working directly with quantitative analysts or data scientists - model development lifecycles, feature pipelines, backtesting, ML deployment, and the rigor to validate what a model is actually doing Capital One is open to hiring a Remote Employee for this opportunity. 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. Remote (Regardless of Location): $244,700 - $279,200 for Distinguished Engineer Cambridge, MA: $269,100 - $307,200 for Distinguished Engineer McLean, VA: $269,100 - $307,200 for Distinguished Engineer New York, NY: $293,600 - $335,100 for Distinguished Engineer Richmond, VA: $244,700 - $279,200 for Distinguished 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).

• Own and drive the development of core systems and performance initiatives from planning and design through implementation and optimization. • Work closely with engineers and cross-disciplinary teams, providing technical leadership and feature ownership. • CPU & Game Thread Optimisation (~25%): Profile and optimise the game thread, render thread, and RHI thread in Unreal Engine — identifies cross-thread bottlenecks, tick overhead, and task graph inefficiency. • Diagnose and resolve hitching: garbage collection pauses, streaming stalls, async loading conflicts, physics simulation spikes. • Reduce tick overhead: identifies UObjects and ActorComponents with unnecessary tick enabled, unnecessary work in hot paths, incorrect tick group assignments. • Optimise gameplay and engine code at the C++ level — not just profiling and handing recommendations to another engineer; writes and ships the fix. • Instruments custom profiling markers (SCOPE_CYCLE_COUNTER, CSV_SCOPED_TIMING_STAT, custom Unreal Insights channels) for ongoing regression detection. • GPU & Rendering Pipeline Optimisation (~25%): Profiles rendering performance using RenderDoc, PIX, NSight, Xcode GPU Frame Capture, and Unreal's GPU Visualiser — isolates draw call overhead, overdraw, shader complexity, and GPU memory bandwidth. • Works with the rendering team to optimise material pipelines: shader permutation reduction, LOD tuning, occlusion culling, distance field shadow optimisation. • Identifies and resolves GPU memory pressure: texture streaming configuration, render target pooling, VRAM budget management per platform. • Understands the rendering architecture deeply enough to distinguish CPU-bound vs GPU-bound vs bandwidth-bound frames and route the fix correctly. • Targets platform-specific GPU constraints: the PS5/Xbox Series GPU architecture differs meaningfully from PC; mobile (Adreno, Mali, Apple GPU) has its own thermal and bandwidth profile. • Memory Profiling & Leak Detection (~20%): Owns memory budget compliance on client engagements: tracks resident set size, texture memory, audio memory, and engine overhead against platform limits. • Finds and eliminates memory leaks in C++ using both automated tooling (ASan, Valgrind on non-console platforms, custom allocator hooks) and Unreal's LLM (Low-Level Memory tracker). • Manages memory fragmentation: understands pooled allocators, custom memory arenas, and when Unreal's default allocation strategy creates fragmentation under long session times. • Console memory work is the hardest version of this: fixed RAM ceilings with no swap. Has shipped inside those constraints. • Builds memory regression tests that run in CI — not just point-in-time snapshots. • Networking / Latency Diagnostics (~10%): Profiles and optimises Unreal's replication system: identifies bandwidth-heavy actors and components, tunes replication frequency, prioritises replication correctly under load. • Diagnoses client-server latency: distinguishes network latency from server frame time from client simulation cost — does not conflate them. • Familiar with NetStat, Unreal's network profiler, and packet-level capture when needed. • Scope: supports multiplayer engagements where networking is a performance constraint — not the primary discipline on pure-networking architecture. • Profiling Tool Development & Automation (~20%): Builds internal profiling tools in C++ (UE plugins) and Python — automated perf validation scripts, CI-integrated regression detection, custom Unreal Insights data channels. • Writes automated performance regression tests: baseline capture, threshold alerting, trend visualisation — so regressions are caught in the build, not in the client review. • Builds or improves developer-facing profiling UX: makes it easier for other engineers on the engagement to find their own bottlenecks without specialist involvement. • Documents profiling methodology and tool usage: other engineers can reproduce the analysis without a knowledge transfer session.