Top Tech Jobs & Startup Jobs

Own the commercial strategy and execution for Protege’s assessments and benchmarking business. Responsibilities include mapping target healthcare AI accounts, managing the existing pipeline, conducting full-cycle commercial engagements, developing GTM strategy, structuring and negotiating deals, coordinating stakeholders, and closing contracts. The role requires fluency in healthcare AI data landscapes, strong pipeline management, and the ability to navigate complex technical, business, and legal discussions.

Partners with executives and managers on workforce planning, organization design, performance management, employee relations, compensation, leveling, culture, and talent decisions. Owns employee lifecycle programs, manager enablement, engagement, communications, HRIS practices, compliance documentation, and scalable People Operations infrastructure. Builds high-performance culture and delivers measurable people-program improvements in a fast-growing technology startup.

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.

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.