Top Tech Jobs & Startup Jobs in NYC, NY

Lead go‑to‑market and close enterprise deals for AI/GenAI healthcare solutions across payers, providers, PBMs, and life sciences. Own revenue targets, shape solutions with architects and product teams, run POCs and demos, craft proposals and pricing, and present ROI/value to CXO stakeholders.

Leads presales solution architecture for complex Life and Annuity insurance and TPA RFI/RFP pursuits. Designs operating models, platform implementations, conversions, integrations, data migration, compliance frameworks, and managed-service solutions. Owns estimation governance, pricing strategy, executive presentations, client discovery, oral presentations, and delivery handoff. Requires deep L&A and TPA operational expertise, major policy administration platform experience, strong estimation and executive communication skills, and knowledge of insurance regulations and privacy requirements.

Leads Neo4j graph database migrations to AWS, including architecture, secure deployment, data integration, performance tuning, query optimization, testing, demonstrations, developer onboarding, UAT, and go-live support. The role requires hands-on expertise with Neo4j, Cypher, AWS infrastructure, ETL tools, graph modeling, benchmarking, and stakeholder communication.

Serves as the senior authority for life and annuity insurance products, pricing, administration, and operations. Partners with actuarial, finance, product, technology, and carrier-client teams to translate product mechanics and pricing assumptions into administration platforms and servicing models. Oversees configuration, testing, migrations, compliance, and financial accuracy while managing client relationships, supporting commercial engagements, and leading a team of product and pricing specialists.

Leads data and analytics transformation strategy for major client programs, defining roadmaps, use cases, architecture direction, and operating models. Advises senior stakeholders, facilitates strategy workshops, aligns programs to KPIs and value frameworks, supports governance and risk management, contributes to proposals and pre-sales, and mentors consulting and analytics teams.

Owns payment integrity quality operations projects from intake through completion, including workflow improvements, system enhancements, testing, validation, reporting, client setup, implementation, documentation, training, and defect resolution. Partners with quality, audit, reporting, technology, configuration, offshore, and end-user teams to improve efficiency, compliance, scalability, data accuracy, and workflow adoption.

Design, implement, automate, and operate enterprise AWS cloud infrastructure for analytics and data engineering workloads. Build Databricks platforms, Infrastructure-as-Code modules, CI/CD pipelines, secure cloud environments, observability frameworks, and multi-account governance strategies. Optimize reliability, scalability, performance, and cost while guiding engineering teams, leading architecture decisions, and advising clients on cloud and DevOps best practices.

Lead and mentor an account management team, develop and execute client retention and growth strategies, build strong client relationships, identify new business, collaborate cross-functionally to deliver insurance solutions, ensure SLAs and compliance, monitor market trends, and drive performance through reviews and coaching.

Leads strategic management and growth of major and global accounts across digital, data, and AI domains. Develops sales plans, identifies expansion opportunities, builds executive relationships, advocates for clients, provides market insight, and mentors junior account managers while driving account performance, revenue growth, and client satisfaction.

Leads multiple life insurance and annuity technology engagements, guiding requirements analysis, solution architecture, technical design, application integration, code quality, and distributed development teams. The role oversees technical delivery, design reviews, documentation, project estimation, process automation, and adoption of emerging AI tools. It requires strong expertise in mainframe technologies, COBOL, SQL databases, C#, .NET, policy administration systems, stakeholder management, and technical leadership.