Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Generate and qualify leads among primary care practices through cold calling, email, and social selling. Assess prospects’ fit for Aledade’s value-based care model, collaborate with sales on outreach strategies, maintain accurate CRM and Outreach.io records, meet lead-generation quotas, and communicate the company’s solutions and value propositions while staying informed about healthcare industry trends.

Leads discovery, definition, execution, and optimization of marketing technology products supporting growth, marketing, and sales teams. Partners with business owners, analysts, developers, and users to define requirements, write user stories, establish measurable success criteria, build roadmaps, and deliver scalable solutions. Uses data, research, and technical understanding to improve workflows, integrate platforms, and drive pipeline and revenue outcomes.

Supports 3–4 senior executives by managing complex calendars, meetings, communications, travel, expenses, onboarding, access permissions, contracts, and operational workflows. Serves as an executive gatekeeper and liaison, coordinates high-stakes engagements, tracks action items, provides technology support, and uses AI tools to streamline administrative processes and improve productivity.

Advise healthcare, product, engineering, and business teams on privacy, HIPAA, data protection, and emerging AI regulations. Own privacy workstreams, review privacy provisions in agreements, support policies and training, manage incidents and regulatory inquiries, monitor legal developments, and partner with compliance, security, and IT teams on risk-based solutions.

Develops scalable data models, Databricks pipelines, backend applications, ETL processes, and data ingestion systems. Partners with engineering, product, and business stakeholders on technical roadmaps; monitors and optimizes data systems for performance, reliability, and scalability. Provides technical leadership, mentors junior engineers, conducts code reviews, and builds secure solutions for sensitive healthcare data.

Own and extend Aledade’s AI enablement platform, including the MCP Gateway, connector integrations, plugin marketplace, model gateway, observability, telemetry, and cost attribution. Build secure authentication and authorization flows, CI/CD and distribution tooling, evaluation harnesses, model routing, and agent collaboration features. Mentor engineers, document platform practices, run enablement sessions, triage requests, and support on-call operations for gateway and marketplace availability.

Lead the roadmap and delivery of an AI data platform supporting internal teams and external healthcare products. Manage ML and LLM platform workstreams across data ingestion, training, deployment, monitoring, and workflow optimization. Partner with AI engineers, researchers, data scientists, clinical leaders, and business stakeholders to define requirements, develop user stories, validate model performance, and turn proofs of concept into scalable production capabilities.

Develop scalable, secure, performant web applications and data pipelines for healthcare technology. Partner with engineering, product, and business stakeholders on technical roadmaps, use Agile practices, improve observability and reliability, and mentor junior engineers through coaching and code reviews. Responsibilities include database querying, technical decision-making, API development, data ingestion, cloud technologies, containerization, CI/CD, and handling sensitive data.

Build scalable full-stack applications integrating healthcare insights with browser-based and Windows EHR systems. Develop products using FHIR and HL7 interoperability standards, collaborate on technical roadmaps, and implement performant solutions. Mentor junior engineers, conduct code reviews, make technical decisions, and partner with engineering, product, and business stakeholders using Agile processes.

Design, implement, and scale web and data pipeline solutions focused on generative AI and LLMs. Improve AI/ML infrastructure for model development, training, deployment, and prompt engineering. Partner with product and stakeholders to prioritize applied AI use cases, ensure PHI security and regulatory compliance, mentor junior engineers, and contribute APIs and integrations to embed generative AI into healthcare applications.