Top Tech Jobs & Startup Jobs

Lead development of generative AI platforms for U.S. government, ensuring ethical deployment and compliance, managing the full product lifecycle, and engaging stakeholders.

Lead strategic initiatives for data collection projects to drive revenue, ensure operational efficiency, and manage diverse global teams.

Design, build, and operate internal tools and applications with a focus on automation and scalability for various users across the organization.

Design and scale multi-cloud infrastructure for an enterprise Generative AI platform. Build integrations with customer cloud/data environments, collaborate with product and customers, deliver experiments to production, and maintain platform reliability and performance.

The Senior Full-Stack Engineer will develop and scale web applications, manage frontend and backend operations, and work with AI systems and databases to enhance product experiences.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.

Lead and scale the support enablement lifecycle: design and deliver onboarding and ongoing training, own QA frameworks and knowledge base, manage a small Enablement & QA team, partner cross-functionally, and track metrics to improve ramp velocity and quality across the support organization.

Build and operate core retrieval and knowledge representation systems for a generative AI platform: design RAG pipelines, embeddings, indexing, vector-store integrations, knowledge graphs/ontologies, evaluation frameworks, and production ML backend services while collaborating across product, ML, and infra teams and shipping enterprise-grade features.

Own the technical health, stability, and operational excellence of production AI deployments for public-sector and enterprise clients. Responsibilities include transition reviews, SLA and incident governance, model and data-drift monitoring, prompt and regression testing, maintenance scope control, model benchmarking, self-healing pipelines, RAG automation, telemetry, and client technical communication. The role requires strong software engineering, MLOps, reliability, cloud, AI governance, and stakeholder-management expertise.

Owns enterprise deal pricing execution, including financial modeling, ROI analysis, staffing inputs, pricing frameworks, and margin reporting. Builds dashboards, coordinates deal reviews across Sales, Finance, Accounting, Legal, and EPD, and tracks approvals and cycle times. Identifies process improvements, supports forecasting and P&L analysis, and contributes to pricing strategy, proposals, and value engineering initiatives.