Top Tech Jobs & Startup Jobs

Post-sales Relationship Manager / Customer Success Manager who onboards and enables customers, drives adoption and value realization, manages renewals and retention, identifies upsell/cross-sell opportunities, delivers training and demos, and coordinates across sales, implementation, and support to ensure customer satisfaction and ROI.

Design, develop, and maintain complex cross-system software; translate user requirements into solutions; implement best practices and development processes; resolve complex technical issues; mentor and train junior engineers; design complex data models and complete difficult bug fixes; participate in specifications, code reviews, and collaborate across teams in various development environments.

Build and own the platform API and internal tooling for real-time EHR sync, FHIR ingestion, and vocabulary normalization. Implement and maintain ingestion pipelines, ensure sync reliability, perform framework upgrades and developer tooling, diagnose production issues, and maintain observability and correctness. Ship production features and own on-call responsibilities for platform subsystems.

Manage and grow B2B customer relationships to protect and increase revenue. Identify customer needs, demonstrate product value, spot upsell/cross-sell opportunities, ensure high-quality customer experience, and coach team members while maintaining planning, reporting, and documentation.

The Solution Sales Manager leads new business development in the EECT market, focusing on data and analytics solutions, builds relationships, develops strategies, collaborates with teams, and manages sales execution to meet revenue targets.

The Senior Sales Compensation Manager will design, implement, and manage sales compensation plans, ensuring alignment with business objectives and compliance with policies. This role includes collaborating with stakeholders and analyzing sales performance data.

Design, build, evaluate, and scale production-ready AI solutions (LLMs, NLP, retrieval, and generative AI) to support scientific discovery. Develop RAG systems, semantic search, summarization, QA, ranking, recommendation, and evaluation frameworks. Integrate knowledge graphs and domain metadata, partner with engineering and product teams, lead technical decisions, and mentor data scientists.

Lead an embedded AI squad from discovery to production: harden and deliver AI prototypes, design reusable agentic AI patterns, ensure security and data governance, integrate AI with enterprise systems, codify reference implementations, mentor engineers, and measure outcomes to scale solutions.

Design and deliver production-ready AI, NLP, and generative-AI solutions (including LLMs and RAG) for knowledge discovery. Build retrieval, ranking, recommendation, and decision-support systems, integrate scientific metadata and ontologies, establish evaluation and monitoring, write production Python code, and provide technical leadership and mentoring.

Lead and develop high-performing data science teams to build AI-powered search, retrieval, NLP, generative AI, and knowledge systems for scientific discovery. Define strategy, drive production deployments, establish evaluation and responsible AI practices, partner with product and engineering, mentor staff, and influence senior stakeholders to deliver measurable impact.