Top Tech Jobs & Startup Jobs

Lead design and implementation of scalable generative AI services and reusable components using Python. Drive architectural decisions, deploy containerized applications on Kubernetes (EKS), ensure scalability/observability and CI/CD, mentor engineers, and collaborate with product and research teams to productionize LLM capabilities.

Own and execute a product feature roadmap, represent customer needs to delivery teams, drive data‑driven decisions, support go‑to‑market activities, engage with customers, and lead cross‑functional collaboration to improve product and business outcomes.

Design, prototype, and operationalize NLP and ML solutions for clinical and scientific content, including entity extraction, relationship extraction, indexing, knowledge graphs, ontologies, and GenAI/RAG POCs. Collaborate with cross-functional teams, manage contractors, mentor interns, and ensure DPR compliance while translating stakeholder needs into production-ready data science solutions.

Manage and grow reseller and key client accounts by developing strategic account plans, building long-term relationships, supporting partners through sales cycles, identifying upsell/cross-sell opportunities, analyzing market trends, and mentoring junior account managers.

Oversee day-to-day data entry operations, manage a small team, ensure accuracy and productivity, monitor metrics, implement process improvements, conduct performance evaluations, allocate resources to meet SLAs, and handle customer-facing data processing interactions.

Lead Public Records strategy and commercial execution for North America, managing a sales team and $14M revenue. Define product strategy, go-to-market, KPIs, and financial models; drive data-driven decisions, product delivery, and cross-functional alignment to capture market opportunities and ensure ROI.

Design, build, and maintain backend services and APIs for document transformation and semantic enrichment. Develop microservices using Java, Spring Boot, and Python, integrate event-driven systems with Kafka and AWS, apply TDD and collaborative engineering practices, support production reliability, and work in a Scrum-based environment to deliver scalable content-processing solutions.

Lead a small-to-medium data science team to design, develop, and deploy advanced AI/ML solutions (especially LLMs/Transformer models), mentor junior staff, define methodologies and governance, collaborate cross-functionally, and set team strategy and high standards for model development.

Designs, develops, and deploys statistical and machine learning models on large structured and unstructured datasets to inform risk segmentation and operational decisions. Leads data acquisition, feature engineering, model experimentation, and productionization while collaborating with stakeholders, mentoring peers, and defining team strategy and milestones.

Designs and executes functional, integration, regression, and load tests; develops automated tests and test plans; identifies root causes and process improvements; collaborates with PMs and technical leads to ensure quality, maintain records for audits, and implement test automation and tooling to improve efficiency.