Trase

Product Designer

• 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.

UX Designer – Contract

AI Engineer

• 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.

Principal Applied ML Researcher – Agentic Systems, Applied AI Platform

Executive Assistant

• 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
• Manage all domestic and international travel booking end-to-end
• Own expense management, including submission and approvals
• Liaise with internal teams and external stakeholders (customers, partners, investors)

• 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.

Senior Staff Technical Program Manager – AI Platform/OS

Backend Engineer

• 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.

Principal Software Engineer – Platform Architecture, Execution Model

Technical Program Manager

• 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.

UX Designer – Contract

Principal Applied ML Researcher – Agentic Systems, Applied AI Platform

Executive Assistant

Senior Staff Technical Program Manager – AI Platform/OS

Principal Software Engineer – Platform Architecture, Execution Model

Staff Technical Program Manager – Industry Verticals, AI Agents