Red Cell Partners

Product Designer

• Partner closely with founders, product, engineering, and leadership to translate ambiguous problem spaces into clear, actionable product design direction.
• Build early concepts and future-state prototypes to test ideas quickly and inform strategy.
• Create and own overall design concepts for the User Experience, for web/mobile/agents/wearables and other emerging modalities, using the latest research and trends to ensure all interactions and designs are intuitive and easy for customers (& investors) to understand.
• Design and ship high-quality products and improvements, from early concepts to high-fidelity prototypes and visuals.
• Personally design and ship work across product UX/UI, prototypes, brand systems, and storytelling.
• Work closely with Marketing on implementing style and branding elements into RCP & its investments’ User Experiences.
• Establish lightweight frameworks, standards, and patterns that enable speed without bureaucracy.
• Help define how design scales as companies mature - from scrappy early builds to durable, repeatable systems.
• Navigate unclear requirements, evolving priorities, and high-stakes decisions with confidence. Balance speed, quality, and pragmatism in fast-moving environments.

Head of Design

• 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.
• 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

Account Executive

• Own early GTM execution, including lead generation, qualification, pilot scoping, and conversion to paid engagements.
• Act as Vantive’s external advocate at events, conferences, and meetings to generate qualified pipeline aligned with GTM priorities.
• Engage directly with prospects to understand pain points, urgency, budget context, and decision criteria.
• Drive pilots and design-partner engagements toward clear commercial outcomes and repeatable customer relationships.
• Shape discovery-driven use cases that inform both product roadmap and GTM positioning.
• Support pre-sales motions including workshops, pilots, and executive briefings.
• Translate platform capabilities into compelling commercial narratives tied to outcomes (risk reduction, revenue at risk, readiness, resilience).

GTM Account Executive

Customer Success Manager

• Own the customer lifecycle: Lead customers through onboarding, implementation, adoption and ongoing success, ensuring time-to-value is fast and measurable
• Partner with SOC Teams: Work directly with analysts, engineers, and security leaders to operationalize Andesite within their workflows.
• Drive Adoption and Value: Ensure customers are actively using the platform and realizing tangible outcomes tied to their security objectives.
• Act as a Trusted Advisor: Engage with both technical stakeholders and security leadership, aligning Andesite to their operational and strategic goals.
• Identify Risk & Expansion Opportunities: Proactively manage account health, mitigate risk, and identify opportunities for growth and expansion.
• Build the CS Function: Help define onboarding frameworks, success plans, health scoring and customer engagement models from scratch.
• Close the Feedback Loop: Partner closely with Product and Engineering to translate customer needs into actionable product insights.
• Support Technical Integrations: Guide customers through integrations (APIs, data sources, workflows) and troubleshoot as needed

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

• 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

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.

Staff Technical Program Manager – Industry Verticals, AI Agents

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

Chief Technology Officer

• Partner directly with our CEO and COO to design, architect, and build the technical foundation that powers Savoy Life’s caregiving-first model.
• Own the creation of our data infrastructure, intelligence layer, and early products that unify caregiving and clinical data—enabling risk stratification, clinical decision support, and scalable continuous care.
• Lead AI/ML-driven capabilities and implement technical strategy for clinical signals, early-risk detection, sentiment analysis, and proactive care workflows.
• Create data integration pipelines and ensure data integrity and traceability across various inputs.
• Build Savoy’s platform with HIPAA compliance and regulatory needs from day one.
• Recruit, mentor, and develop engineers as the organization scales and establish engineering culture, SDLC practices, architectural standards, and performance expectations.

Founding CTO, Healthcare Startup

Software Engineer

• Build the Platform From Scratch
• Partner with our founder to design and build Version 1 of the health intelligence platform. You'll make foundational technical decisions that shape the product for years to come.
• Architect the Health Intelligence Engine
• Build the backend infrastructure, APIs, and data models that power personalized health insights. Design systems that synthesize lab results, wearable data, symptoms, and medical history into actionable intelligence.
• Develop Data Integration Pipelines
• Create robust ETL pipelines to ingest data from diverse sources: lab providers (Quest, LabCorp), wearables (Oura, Apple Health, Whoop, Garmin), medical records, and user-entered data. Ensure data integrity, security, and HIPAA compliance.
• Build AI-Powered Features
• Implement the conversational AI health check-ins, treatment recommendation engine, and predictive models that surface insights and guide users through their health journey. Work with Claude and other AI tools to accelerate development.
• Own Security and Compliance
• Build with HIPAA compliance from day one. Implement encryption, access controls, audit logging, and security best practices for handling sensitive health data.
• Leverage AI-Native Development Tools
• Use Claude, Claude Code, Cursor, and other AI-assisted development tools to accelerate building. Embrace vibe coding and rapid prototyping to move quickly from concept to working product.
• Grow Into Leadership
• As we scale, mentor and guide additional engineers. Help establish engineering culture, practices, and standards. This role has a clear path to engineering leadership.

Founding Engineer, Architect – Stealth Healthcare Startup

Machine Learning Engineer

• Build Core Platform Features: Develop backend services, APIs, and user-facing features across the platform. You'll work on everything from symptom tracking to lab result visualization to treatment recommendations.
• Integrate Data Sources: Build integrations with wearables (Oura, Apple Health, Whoop, Garmin), lab providers, and other health data sources. Create pipelines that ingest, normalize, and store data reliably.
• Contribute to AI/ML Systems: Work alongside senior engineers to build and improve our health intelligence engine—including conversational AI, recommendation models, and pattern detection. Prior ML exposure is helpful; willingness to learn is essential.
• Ship Fast and Iterate: We're early stage. You'll ship code frequently, get feedback from real users, and iterate quickly. Comfort with ambiguity and a bias toward action are key.
• Build with AI-Native Tools: Use Claude, Claude Code, Cursor, and other AI-assisted development tools daily. We embrace vibe coding and expect you to leverage AI to move faster and learn faster.
• Learn the Healthcare Domain: You'll pick up health data concepts, compliance basics (HIPAA), and clinical terminology as you go. We'll support your learning—curiosity matters more than prior experience here.

Founding ML Engineer – Stealth Healthcare Startup

Full-stack Engineer

• Shape the product architecture end-to-end.
• Own the data foundation.
• Engineer for performance at scale.
• Drive technical direction through RFCs.
• Ship with product and design, not in a silo.
• Use AI as a force multiplier (responsibly).
• Hold the quality bar high.