Bedrock Talent - Lead AI Engineer, Stealth Longevity AI Startup
Requirements
• 6+ years of software engineering experience, including full-stack web application development, relational database design, event-driven systems, and cloud-based production environments • Recent, meaningful experience using AI coding tools and agents, such as Claude Code or comparable platforms • Bachelor’s or master’s degree in computer science, or equivalent practical experience • Experience working on highly collaborative, small engineering teams within high-growth startup environments • Interest in helping lead and mentor a small team while remaining deeply hands-on • Experience building and productionizing LLM, generative AI, or other AI-driven applications • Experience in healthcare technology, digital health, or another regulated environment • Demonstrated success delivering production SaaS or platform-based products • Strong knowledge of modern software development practices, CI/CD, microservices, cloud infrastructure, and production operations • Ability to quickly understand and take ownership of existing production systems • Proven ability to operate effectively amid ambiguity, rapid change, and evolving priorities • Exceptional communication skills and genuine enthusiasm for working in a mission-driven environment • Enjoys collaborating closely with Product and Design • Experience working with Model Context Protocol tools or MCP-based environments • Familiarity with healthcare security, compliance, and audit requirements • Experience partnering with Product, Data Science, Medical, or Research teams • Experience helping a startup scale through the Series A or Series B stage • Experience with healthcare data sources, including claims, EHR, clinical, genomic, or longitudinal datasets • Success in the First 12–24 Months • MVP and early product milestones are delivered on time • The company has a stable and reliable platform supporting early customers • QA, testing, and release discipline are embedded throughout the engineering lifecycle • Product, Data Science, Operations, and Engineering work together effectively • AI and analytical systems are explainable, testable, observable, and production-ready • The company has strong technical and operational foundations in place for Series A growth
Responsibilities
• Platform and Agent-Based Architecture • Lead the design and implementation of the company’s AI-first platform architecture, including: • Agent-based systems, such as matching, reasoning, and orchestration agents • Model orchestration layers and inference pipelines • Data ingestion, transformation, and feature pipelines • Build and operationalize systems supporting: • Proprietary analytical framework execution • Cohort matching and comparative analysis • Longitudinal and temporal data analysis • Ensure systems are modular, extensible, and designed to support future scale • Engineering Execution and Delivery • Own engineering execution and delivery across product initiatives and company milestones, including work completed with external resources and partners • Translate product requirements, PRDs, and user stories into clear technical plans and deliverables • Drive sprint planning, execution, and delivery in close partnership with Product • Establish a predictable release cadence while balancing speed, quality, and technical debt • Quickly understand, improve, and take ownership of existing production systems • Technical Leadership and Architecture • Serve as the company’s senior hands-on engineering leader in partnership with the CTO • Make pragmatic architecture and technology decisions appropriate for an early-stage environment • Design systems for future scalability, security, and compliance without over-engineering • Establish technical standards, documentation, and engineering best practices • Help lead and mentor a small engineering team as the company grows • AI/ML Productionization and MLOps • Partner closely with Data Science leadership to productionize models and analytical frameworks • Implement MLOps and LLMOps practices, including: • Evaluation harnesses • Prompt and version management • Retrieval-quality monitoring • Output grounding and citation integrity • Latency and token-cost monitoring • Ensure models and AI systems are: • Scalable and performant • Reproducible and testable • Observable and auditable • Reliable in production environments • Quality Assurance and Reliability • Own engineering quality and QA execution throughout the development lifecycle • Establish testing practices for: • AI and machine-learning systems • APIs and integrations • Full-stack product functionality • Implement CI/CD pipelines, automated testing, and release-readiness gates • Ensure system reliability, performance, and observability • Data Infrastructure, Compliance, and Integrations • Design and implement infrastructure for integrating with EHR data, claims data, longitudinal healthcare datasets, and relevant research or genomic data sources • Partner with Data Science and Product to ensure engineering practices support healthcare privacy and security expectations • Ensure the platform supports HIPAA-aligned data handling and security practices • Collaborate with Operations leadership on compliance-related technical requirements • Build secure, scalable integrations with external systems and data partners • Cross-Functional Collaboration • Work closely with the CTO and COO to align engineering execution with company priorities • Partner closely with Product on requirements, scope tradeoffs, and delivery timelines • Collaborate with Data Science, Medical, and Research leaders to translate scientific direction into technical implementation • Support customer implementation and service teams with technical onboarding, integrations, and issue resolution • Communicate technical decisions, risks, and tradeoffs clearly to both technical and nontechnical stakeholders • Release Management and Incident Response • Own release planning, deployment readiness, and rollback strategies • Monitor production performance, uptime, and system health • Lead incident response and postmortem processes • Drive continuous improvements in reliability, observability, and operational readiness • Operations and Execution Discipline • Contribute to lightweight operating rhythms, including planning sessions, execution reviews, and retrospectives • Surface technical and execution risks early and recommend practical solutions • Partner with Operations leadership on resourcing, sequencing, and delivery tradeoffs • Create enough structure to support reliable execution without slowing down an early-stage team
Benefits
• $180K – $200K • Offers Equity • We believe compensation should be fair, competitive, and consistent. We benchmark our salaries against the market, reward impact over negotiation, and strive to make compensation decisions that are equitable, transparent, and aligned with each person's role, experience, and contributions. As an early-stage company, we also believe meaningful equity allows everyone to share in the long-term success of what we're building together. • Remote (U.S.) | Travel as Needed • At Bedrock Talent, we're intentional about the companies we represent. • We don't partner with every startup that comes our way. We work with founders we'd be excited to work for ourselves, companies solving meaningful problems, and teams we genuinely believe have the potential to build category-defining businesses. • This is one of those companies. • Our client is an early-stage healthcare AI company on a mission to improve health outcomes by leveraging artificial intelligence, data science, and clinical expertise to generate meaningful, actionable insights from complex health data. • The team is building an AI-native platform designed from the ground up—not by retrofitting AI onto existing software, but by making intelligent systems the foundation of the product. Working alongside experienced founders, healthcare leaders, and world-class advisors, you'll have the opportunity to help define both the technology and the company itself. • The company offers a competitive salary, meaningful early-stage equity, comprehensive healthcare benefits, generous PTO, and ongoing professional development support. • More importantly, this role offers the opportunity to help build the technical foundation of a company at a stage where your impact will be visible for years to come. • The best engineering opportunities don't come from maintaining someone else's architecture—they come from building your own. • This is one of those opportunities. • You'll help define the technical foundation of an AI-native healthcare platform, work alongside exceptional founders and technical leaders, and play a pivotal role in building technology that has the potential to improve healthcare at scale. • If you're excited by ownership, ambiguity, and building AI systems that solve meaningful problems, we'd love to connect.
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