Top Tech Jobs & Startup Jobs

Lead the evolution of technology learning strategies by consulting with leadership, identifying skill gaps, developing innovative learning solutions, and building cross-functional frameworks to improve product quality and team competencies.

The Sr. Analyst role involves leading HR data analyses, building analytical capabilities, designing reports, and educating stakeholders on data tools.

The Data Science Manager leads data scientists in enhancing business profitability and customer experience, managing projects, and collaborating across teams. Responsibilities include mentoring, strategizing, and developing technical skills within the team.

The Sr. Product Manager focuses on assessing market needs, delivering business value, managing product strategy, and collaborating with cross-functional teams to improve customer satisfaction and drive sales.

The Senior Developer, Item Data, will architect data pipelines, create dashboards, and support data integrity to drive strategic insights across the enterprise.

Lead UX strategy and execution across product domains, craft end-to-end experiences, drive alignment with product and business goals, mentor junior UX staff, and deliver UX artifacts (experience maps, service blueprints) while partnering with cross-functional teams to champion user research and design standards.

Manage financial planning, budgeting, cost controls, and reporting for reset projects. Support project processes (inventory, purchasing, logistics, systems), define business requirements for project tools, perform financial and root-cause analysis, and coordinate cross-functional stakeholders to ensure project goals and budget compliance.

Owns end-to-end learning programs for leadership development, including design, delivery, vendor management, LMS deployment, and measurement. Partners cross-functionally to identify learner needs, drive change management, forecast demand, manage budgets, and continuously improve program effectiveness and participant experience.

Owns product strategy and delivery for an enterprise product line: translate customer needs into roadmap, prioritize user stories, run user research and testing, measure product value, collaborate with engineering, UX, and stakeholders, and support cross-functional execution to drive sales and customer satisfaction.

Design, build, and scale production-grade agentic AI systems using LLMs, RAG, and multi-agent orchestration. Implement cloud-native MLOps (Docker, Kubernetes, Terraform), CI/CD, observability, and reliability practices. Partner with product and engineering to prototype, deploy, monitor, and optimize AI solutions for enterprise use.