Top Tech Jobs & Startup Jobs

Leads enterprise CDN and edge-delivery architecture, automation, web performance, DNS, traffic management, and application security engineering. Builds reusable infrastructure, APIs, GitOps workflows, CI/CD pipelines, and self-service tooling. Provides operational support through on-call participation, incident leadership, release support, root-cause analysis, and remediation. Defines modernization roadmaps, improves reliability and performance, leads technical initiatives, and mentors engineers across application, cloud, network, infrastructure, security, and vendor teams.

Leads the design, development, testing, deployment, maintenance, and support of scalable Java microservices and full-stack applications. Serves as a technical lead and subject matter expert, translates business requirements into technical solutions, promotes software engineering best practices, supports production systems, and mentors Java developers. The role collaborates with architecture, development, operations, and business teams across the full product lifecycle.

Leads the vision, strategy, roadmap, and lifecycle for Health100 digital health experiences spanning conversational AI, care coordination, wellness, and ongoing treatment. Owns AI assistant capabilities, member wellness and care navigation experiences, product guardrails, safety, privacy, and responsible data use. Partners across Product, Design, Engineering, Clinical, Legal, Operations, and business teams to launch, measure, and optimize trusted, personalized consumer health products.

Architects, develops, tests, debugs, and optimizes scalable software applications and digital solutions. Participates in architecture discussions, code reviews, technical decision-making, and adoption of engineering best practices. Collaborates cross-functionally to deliver complex features, contributes to technical direction, shares knowledge, and mentors junior developers. Preferred experience includes cloud platforms and systems leveraging GenAI capabilities.

Leads the Finance Technology AI Enablement engineering team, setting technical strategy and delivering AI, ML, and GenAI solutions. Responsibilities include managing and mentoring engineers, translating business needs into technical roadmaps, overseeing concurrent initiatives, establishing scalable architecture and DevOps practices, and ensuring governance, security, privacy, and compliance. The role also advises stakeholders on AI adoption, enables low-code and full-stack solutions, and reports program value and risks to senior leadership.

Designs, builds, and operationalizes secure, scalable generative AI and machine learning systems across AWS and GCP. Responsibilities include developing LLM, agentic, and RAG applications; architecting serverless, event-driven microservices; managing model experimentation, evaluation, deployment, and monitoring; and optimizing performance and cost. The role also leads responsible AI, HIPAA compliance, governance, and technical collaboration while mentoring engineers and managing team performance.

Develop risk prediction models using large-scale healthcare data, advanced statistical methods, machine learning, SQL, Python, R, Spark, and cloud computing. Analyze structured and unstructured data, identify patterns, validate models, assess risk, and communicate insights to business stakeholders. The role also emphasizes practical use of AI tools and understanding of large language models.

Develop and maintain databases, data sources, analytical tools, and data models supporting actuarial, finance, underwriting, and medical economics teams. Build well-documented code, analyze detailed healthcare datasets, communicate findings to technical and business stakeholders, and deliver solutions across Commercial, Medicare, and related domains.

Leads enterprise learning technology implementations, configurations, integrations, data migrations, validation, testing, and optimization. Manages LMS and LXP platforms, coordinates vendors and technical teams, defines requirements and data flows, oversees UAT and pilot rollouts, resolves platform issues, and communicates status to stakeholders. Provides direction to analysts and contractors while supporting AI-enabled learning tools and multiple concurrent initiatives.

Leads AI engineering strategy, architecture, agentic frameworks, AI SDLC, operating models, governance, and production AI delivery across payer and TPA businesses. Builds and mentors high-performing AI engineering teams, establishes enterprise standards, partners with security, compliance, data, and architecture teams, and advises executives on AI investments, risks, technology selection, and measurable business value.