Top Tech Jobs & Startup Jobs

Lead a team of software engineers and a portfolio of technology projects, building cloud-based full-stack and distributed microservices solutions. Develop and mentor engineers, collaborate with product managers, address regulatory needs, and use Python, JavaScript, Java, TypeScript, SQL, Go, AWS, Docker, Kubernetes, and database technologies. The role also emphasizes network automation, cloud engineering, Agile practices, and adoption of emerging technologies.

Supports multiple senior executives through complex calendar management, travel coordination, expense reporting, team events, information distribution, and relationship building. The role requires strong organization, communication, judgment, adaptability, multitasking, and proficiency with office productivity and collaboration tools.

As a Data Scientist, you'll analyze complex datasets to optimize fraud authentication, design ML solutions, and collaborate with cross-functional teams.

Lead a team of software developers and oversee diverse technology projects involving distributed microservices and full-stack systems. Build robust cloud-based solutions supporting regulatory requirements and customer experiences. Use Java, Go, Python, JavaScript, TypeScript, SQL, AWS, Docker, Kubernetes, RDBMS, and NoSQL databases. Mentor engineers, collaborate with product managers, evaluate emerging technologies, and drive delivery in an Agile environment.

Leads project management and technical integration for corporate partners, coordinating internal and third-party technology teams. Responsibilities include translating business needs into technical solutions, managing risks and controls, improving processes, supporting agile requirements, ensuring service quality, communicating with stakeholders, and removing delivery impediments. The role requires project or process management and systems integration experience, with preferred experience in data analytics, SQL, business intelligence tools, AWS, and Agile or related methodologies.

Leads a project management team responsible for well-managed controls and L2 process oversight across customer service platforms. Owns end-to-end processes, risk controls, operational resilience, stakeholder alignment, process automation, audit improvements, and strategic delivery execution. Partners with Risk, Product, Technology, and Data teams to improve efficiency, compliance, and platform reliability while coaching team members and driving scalable process innovation.

Lead strategic, data-informed communications programs for Premium Products and Experiences. Advise internal leaders, craft targeted messaging, manage cross-functional campaigns, mitigate reputational risk, measure outcomes, and oversee team operations to drive brand and business objectives.

Design, build, deploy, scale, and maintain production machine learning systems and models. Lead technical design, model and application development, data pipeline construction, cloud architecture, testing, CI/CD, monitoring, governance, and responsible AI practices. Collaborate with Product, Data Science, and Agile engineering teams while leading teams developing enterprise AI coding tools.

Lead software asset management execution, including license compliance reconciliations, Effective License Position analysis, software reclamation, entitlement and installation reviews, audit support, and asset data normalization. Maintain software catalogs, publisher and SKU records, resolve discovery and procurement discrepancies, and author operating procedures, process maps, workflows, and policies governing enterprise software management. The role also requires leadership experience and familiarity with DevOps tools, AWS, ServiceNow, and SAMPro.

Leads the design, development, deployment, and maintenance of machine learning systems at scale. Responsibilities include building ML models and data pipelines, writing production code, optimizing cloud architectures, automating testing and deployment, monitoring and retraining models, and ensuring performance, governance, security, responsible AI, and explainability. The role collaborates with Product and Data Science teams in an Agile environment focused on enterprise AI coding tools.