Jobs at Protege

Build the technical foundation for a new business vertical, including reusable infrastructure, integrations, workflows, and tooling. Lead early customer engagements from technical scoping through delivery and support, translate customer needs into durable systems, and partner with Product and Engineering to productize repeatable capabilities. The role requires strong backend and data engineering instincts, comfort with ambiguity, and the ability to balance rapid delivery with long-term architecture.

Develop product positioning, messaging, content, and go-to-market assets for an AI training data platform. Lead end-to-end product, vertical, DataLab, and commercial launches; translate complex AI and data concepts for technical buyers; create thought leadership, case studies, decks, webinars, videos, social content, and landing pages; and partner with Product, Sales, DataLab, Community, and business leaders to strengthen market narrative and support commercial growth.

Own technical delivery for video customers from feasibility through post-delivery support. Translate ambiguous requirements into technical plans, build and operate scalable video data processing and delivery systems, improve dataset measurement and quality tooling, and turn recurring customer needs into reusable platform capabilities. The role requires managing multiple concurrent engagements, partnering across product, engineering, data, and commercial teams, and developing video-specific playbooks, standards, and infrastructure.

Build and maintain a qualified pipeline of healthcare data partners through market mapping, outbound prospecting, inbound triage, discovery, and opportunity qualification. Research data holders, assess dataset quality and commercialization fit, prepare handoff briefs, maintain Salesforce pipeline hygiene, track sourcing metrics, and provide market insights to guide partnership strategy and prioritization.

Manage healthcare data partners from qualification through sample evaluation, activation, deal structuring, and ongoing engagement. Conduct discovery and due diligence, coordinate NDAs and sample intake, assess and tier partners, socialize data assets internally, support pricing and statements of work, and facilitate transitions into operations. Develop portfolio growth strategies, maintain partner relationships, identify market opportunities, systemize workflows, and use deal activity and market signals to improve partnership scalability.

The Senior Software Engineer will design and operate data ingestion and processing systems for multimodal data, ensuring quality, security, and compliance while optimizing for performance and reliability. Responsibilities include building pipelines, handling messy data, and partnering with teams to enhance the platform's capabilities.

As a Forward Deployed Engineer, you'll define market technical needs, build reusable infrastructure, lead customer engagements, and shape product capabilities in a new AI vertical.

Own full-cycle recruiting for multiple technical roles, from intake through offer close. Partner with hiring managers and leadership to define requirements, develop sourcing strategies, assess candidates, provide market intelligence, and improve recruiting processes. Build pipelines for difficult-to-fill engineering, AI/ML, infrastructure, data, and security positions while delivering a high-touch candidate experience and supporting scalable hiring practices.

The Machine Learning Researcher will design datasets and evaluate environments for agentic systems, focusing on data quality and benchmarking model performance in RL settings. They will collaborate with teams to translate workflows into evaluative frameworks and improve the understanding of high-quality datasets.

Own day-to-day AP and AR workflows, prepare domestic and international wires, support collections, maintain cash tracking and financial records, coordinate vendor payments, and improve finance processes and controls while working with the Controller and CFO.

The Director of Research will lead DataLab at Protege, defining the research agenda and managing a high-performing team focused on AI data challenges and methodologies.

Build benchmarks and eval infrastructure for real-world AI evaluation. Partner with researchers and customers to design benchmarks, process multimodal data, build data pipelines, sandboxed execution environments, storage, and orchestration. Ship iterative eval infrastructure and own engineering for customer engagements.

Build and ship end-to-end features for internal dashboard and customer portal in a TypeScript/Next.js stack. Design UIs, implement APIs, data models, tests, media playback, embedding-based search, secure access controls, and work with large multimodal datasets across Postgres and AWS.

Own the supply-side product for data ingestion and quality: design ingestion stages, validation gates, metadata generation, QA standards, and catalog-readiness. Work hands-on with raw data and pipeline outputs, write SQL, define platform requirements, and align cross-functional stakeholders to make external partner data trustworthy and repeatable across verticals.

Own and grow a small portfolio (2-4) of strategic foundation-lab and frontier AI accounts. Build multi-year deal strategies, map stakeholders, coordinate internal teams (DataLab, Solutions, Legal, CSM), and drive significant GMV through structured agreements, accurate forecasting, and expansion opportunities. Represent Protege at events and surface account-derived insights to shape product and supply strategy.

Build and ship end-to-end UI and backend features for Protege's internal dashboard and customer portal in a TypeScript/Next.js codebase. Design complex, data- and media-heavy workflows, optimize streaming and previews, implement APIs and data models (Postgres, AWS), ensure secure handling of sensitive data, mentor the team, and turn UI patterns into reusable design-system components.