Trase

• Define and evolve the long-term AI/ML research strategy and technical roadmap for Trase OS in alignment with product and platform direction. • Lead large-scale experimentation and prototyping efforts requiring significant compute infrastructure, translating frontier AI research into scalable, production-grade systems with measurable impact. • Drive original research and technical breakthroughs in agentic systems, autonomous execution, multi-agent orchestration, post-training and fine-tuning systems, SLM/LLM-based architectures, and applied AI infrastructure. • Design how models operate within long-lived execution environments, including agent workflows, tool use, planning, memory systems, reasoning, and human-in-the-loop controls. • Establish evaluation methodologies and reliability frameworks for autonomous systems, including benchmarking, regression testing, safety, controllability, and production behavior analysis. • Drive architecture decisions across orchestration, model serving, routing, inference, and infrastructure governance, including latency, reliability, and cost optimization. • Partner closely with engineering and product teams to operationalize research outcomes into deployable systems and enterprise workflows. • Build AI systems that operate reliably in regulated and constrained environments, including secure cloud, on-premise, and air-gapped deployments. • Contribute to the broader AI research community through technical papers, publications, conference participation, architecture proposals, and thought leadership. • Serve as a senior technical authority and mentor across the organization, influencing technical direction, research rigor, experimentation practices, and best practices across research, engineering, and product teams.

• Provide dedicated support to the President and CTO • Act as a true gatekeeper—prioritizing time, managing interruptions, and confidently saying “no” when needed • Proactively manage and plan upcoming priorities, including shaping agendas weeks to months in advance • Track fast-moving commitments (e.g., external engagements) and ensure executives are prepared and present • Own complex calendars with constant changes (“calendar churn”) • Coordinate meetings across multiple time zones (U.S. and global) • Navigate last-minute changes with speed and sound judgment • Ensure executives have space for focus time, breaks, and realistic schedules • Manage all domestic and international travel booking end-to-end • Make smart, experience-based decisions (e.g., balancing cost vs. practicality—not defaulting to impractical early flights) • Align travel with business priorities and executive well-being • Own expense management, including submission and approvals • Ensure accuracy, timeliness, and alignment with company policies • Take full ownership of this process to reduce executive overhead • Liaise with internal teams and external stakeholders (customers, partners, investors) • Track down and coordinate executives when needed across competing priorities • Represent leadership with professionalism and clarity • Take on office administration responsibilities as the Seattle office launches • Support office setup, vendor coordination, and ongoing operations • Help establish processes and structure for a growing team • Support planning of company events (e.g., offsites, team gatherings, board meetings) • Initially a lighter lift, growing over time; partner with the broader team to execute • Help manage budgets and logistics for these events • Build and improve administrative processes as the company grows • Partner with Operations on scaling systems and workflows • Potential to support light business operations work over time (not a primary responsibility initially)

• Partner with Sales on discovery calls, technical deep-dives, and evaluations; clarify requirements and success criteria. • Translate customer problems into product use cases, solution approaches, and scoped implementation plans. • Explain Trase’s platform and agent capabilities to technical and non-technical stakeholders. • Build rapid demo mock-ups and proof-of-concepts (including lightweight “cloud code”/scripted demos) to validate workflows and accelerate deals. • Own and evolve demo assets: reusable scenarios, sample data, reference architectures, and competitive positioning. • Write clear artifacts: requirements summaries, solution proposals, architecture diagrams, and handoff docs for delivery teams. • Partner with Product on feedback loops: surface recurring needs, prioritize gaps, and propose roadmap opportunities grounded in customer signal. • Support delivery handoff: ensure Engineering has the context needed to implement what was sold (and that commitments match reality).

• Build and operate Clay workflows that research, enrich, and score 121+ target hospital accounts automatically. • Configure intent signals (Unify) and respond to buying triggers—new CMIO hires, AI strategy announcements, RFPs—within 4 hours with AI-personalized outreach. • Design and optimize Apollo outreach sequences; A/B test messaging; track conversion rates by tier and channel. • Build the pre-conference outreach machine for ASTRO, HIMSS, and ACRO—scheduling 15–25 meetings before each event. • Generate AI-powered meeting prep briefs and post-call follow-ups so senior sellers stay focused on closing. • Maintain Salesforce as the source of truth and report weekly on what’s working, what’s not, and what’s changing. • Document everything you build so this function can scale.

• Own and close net-new enterprise logos across non-acute healthcare segments, from first meeting through contract signature and expansion. • Navigate complex organizations—identifying executive sponsors, economic buyers, clinical champions, compliance stakeholders, and IT decision-makers. • Lead value-driven sales cycles grounded in customer workflows, regulatory pressures (HIPAA, CMS, prior authorization), and operational pain points specific to each healthcare segment. • Build ROI models and business cases tied to cost reduction, throughput, risk mitigation, claims accuracy, and revenue lifecycle optimization. • Design and run tight, outcome-based POCs with clear success criteria and executive alignment. • Build and execute territory and account plans to generate pipeline and deliver predictable ARR. • Collaborate with GTM Engineers, Product, Engineering, and Executive Leadership to advance deals and ensure successful handoffs. • Provide structured market feedback that informs product roadmap and GTM strategy.

• Design intuitive, user-centered experiences for agent-facing workflows and tools. • Create UX flows, wireframes, prototypes, and interaction patterns for demos and product features. • Partner with product managers and engineers to translate requirements into clear, functional designs. • Ensure consistency across all UX touchpoints, including demos, internal tools, and agent experiences. • Lead UX and visual design for the company website, ensuring clarity, usability, and brand alignment. • Produce marketing materials including landing pages, digital assets, and campaign visuals. • Support marketing initiatives with design for events, announcements, and promotional content. • Design and refine executive presentation decks, including executive decks for internal and external audiences. • Create visually compelling materials for conferences—both UX and technical—including slides, signage, and demo visuals. • Ensure all conference design aligns with product messaging, brand identity, and audience needs. • Own the UX and visual design for all product demos. • Develop cohesive demo flows that clearly communicate product value and functionality. • Collaborate with product and engineering to ensure demo environments reflect real-world use cases. • Work closely with product managers, engineers, and marketing leads to understand needs and translate them into thoughtful UX solutions. • Maintain and evolve design systems and brand guidelines across product and marketing surfaces. • Manage multiple projects simultaneously while meeting deadlines in a dynamic environment.

• Drive technical breakthroughs in agentic systems, applied ML infrastructure, and LLM-based applications. • Define and evolve the ML/LLM strategy and technology roadmap in alignment with product development. • Act as a principal technical authority, making high-impact architectural and modeling decisions across teams. • Develop prototypes for key technologies to validate new approaches and de-risk system design. • Own the full lifecycle from research and experimentation through production deployment, monitoring, and iteration. • Translate advances in ML into scalable, production-grade systems with measurable impact. • Design how LLMs operate within agent workflows, tool use, and multi-step reasoning and long-lived execution. • Implement and refine prompting strategies, multi-agent orchestration, memory management, and human-in-the-loop controls for safety and reliability. • Establish patterns for planning, decision-making, and tool orchestration within complex systems. • Own end-to-end quality evaluation of ML-powered systems, including defining metrics, benchmarks, and testing frameworks. • Establish evaluation systems that connect model performance to task success and system-level outcomes. • Ensure systems behave predictably, safely, and reliably in production through monitoring, regression testing, and robust failure handling. • Contribute to the design of ML systems supporting the full lifecycle, including training, fine-tuning, evaluation, deployment, and monitoring. • Drive architecture decisions across model serving, routing, orchestration, and latency and cost optimization. • Work across infrastructure layers, including cloud and containerized systems, to ensure scalable and efficient deployment. • Build and deploy enterprise-grade AI systems used by global customers in production environments. • Design systems that operate reliably in regulated and constrained settings, including on-premise, air-gapped, and secure cloud environments. • Ensure systems are auditable, explainable, and compliant with regulatory and organizational requirements. • Write technical reports and design documents summarizing R&D progress, system behavior, and key decisions. • Communicate complex ML concepts and tradeoffs clearly to both technical and non-technical stakeholders. • Drive alignment across research, engineering, and product through strong technical leadership. • Mentor junior and senior engineers and researchers, raising the bar for ML rigor and system-level thinking. • Establish and propagate best practices for ML system design, evaluation, and reliability across the organization. • Influence technical direction beyond immediate teams through high-impact, cross-functional work.

• Architect & lead the core execution model (state machine, lifecycle, resource model, failure semantics) • Design platform APIs/SDKs connecting workflows, agents, tools, and product surfaces; drive versioning & compatibility • Guarantee correctness via idempotency, deterministic replays, compensating actions, and data integrity • Engineer reliability at scale: concurrency controls, rate limits, backpressure, sharding/partitioning, and workload isolation • Build security & governance into the core: RBAC/ABAC, policy enforcement, fine-grained audit & lineage • Deliver observability: distributed tracing, structured logs, metrics, and evaluation hooks; build an “explainable trail” of agent actions • Own quality: design reviews, test strategy (unit, property, chaos), performance baselines, SLOs, incident response, and postmortems • Mentor & unblock senior engineers; partner with Product, Security, and Customer teams to translate requirements into durable primitives • Make pragmatic choices on storage, queueing, and compute; create paved roads that accelerate all other teams • Define system boundaries and reduce cross-service coupling through clear architectural patterns • Drive platform-wide standards for correctness, reliability, and API design across teams • Balance short-term delivery with long-term architectural integrity, ensuring the platform evolves without accumulating systemic risk.

• Own end-to-end execution of customer-facing programs across national security, healthcare, and enterprise verticals, translating ambiguous customer requirements and platform capabilities into clear, actionable delivery plans. • Coordinate customer milestones, integration timelines, and deployment readiness across engineering, DevOps/SRE, and external stakeholders, ensuring alignment on scope, sequencing, and success criteria. • Manage compliance and security-driven constraints (e.g., RMF/ATO processes, HIPAA considerations, enterprise security requirements), ensuring delivery plans account for approval cycles, evidence generation, and audit readiness. • Identify and manage cross-team and cross-environment dependencies (platform services, infrastructure, integrations), reducing integration risk and preventing delivery delays. • Establish and maintain execution cadence for customer programs, including milestone tracking, readiness reviews, stakeholder updates, and escalation paths. • Drive release and deployment readiness across environments (cloud, VPC, on-prem), ensuring systems are validated, secure, and operationally ready before customer delivery. • Partner with DevOps/SRE to ensure incident readiness, monitoring, and operational procedures are in place for customer deployments, particularly in high-assurance environments. • Act as the central point of accountability for delivery status, risks, and tradeoffs across customer programs, ensuring transparency and proactive risk mitigation.

• Own end-to-end execution of internal platform initiatives across the Trase operating system, translating ambiguous work across infrastructure, runtime systems, and AI/ML workflows into clear, actionable plans while ensuring alignment across Engineering, DevOps/SRE, DevEx, and Product. • Identify and manage cross-team dependencies across services, cloud infrastructure, and AI pipelines, sequencing work to minimize blocking dependencies, reduce integration risk, and avoid rework. • Establish and maintain a lightweight operating rhythm that drives execution, including milestone tracking, execution reviews, and release readiness checkpoints, ensuring teams have clear priorities, defined success criteria, and visibility into risks. • Partner with DevOps and SRE to ensure releases are safe, validated, and traceable, and that platform and AI/ML changes are observable, auditable, and ready for production environments; drive go/no-go decisions based on system readiness and risk. • Proactively identify and manage system-level risks across infrastructure, deployment systems, AI/ML pipelines, and runtime behavior, ensuring mitigation strategies are in place before issues impact delivery. • Define and track key execution and reliability signals, including delivery predictability, release success rates, dependency resolution, and system health, acting as the source of truth for execution status and risk. • Continuously improve engineering execution by identifying inefficiencies in CI/CD workflows, testing and integration systems, and AI workflow evaluation, partnering with DevEx and DevOps to increase developer velocity, release safety, and overall system reliability.