Top Tech Jobs & Startup Jobs

Manage strategic mid-market and enterprise SaaS accounts by driving product adoption, customer value, retention, renewals, and relationship growth. Develop account success plans, conduct business reviews, monitor usage and risk trends, educate customers on new features, coordinate internal stakeholders, resolve issues, and communicate customer feedback to product and service teams.

Drive DevOps and SRE initiatives across cloud-native data infrastructure. Deploy and manage Kubernetes workloads on AWS and GCP, provision infrastructure with Terraform, maintain CI/CD pipelines, develop Python automation, improve observability and reliability, optimize cloud costs, enforce security standards, and influence cross-functional data and engineering teams.

Build Python-based agentic developer productivity systems that transform engineering requests into scoped work, implementation plans, testing, reviews, and pull requests. Develop Slack, Jira, Salesforce, and workflow integrations; support distributed systems, permissions, auditability, observability, rollback, and cost controls. Collaborate cross-functionally, write maintainable code, participate in reviews, use AI-assisted development tools, and troubleshoot agentic platforms.

Lead development of AI-native GTM products using LLMs and autonomous agents. Set vision and roadmap, partner with sales/marketing/CS, define AI metrics, run experiments, and lead cross-functional teams to deliver revenue-driving, user-centric automation.

Design, develop, and maintain scalable backend and full-stack systems using Java, Node.js, NestJS, Kafka, REST APIs, and cloud technologies. Build and improve microservices, databases, and event-driven applications while enhancing performance, security, and maintainability. Collaborate with product, engineering, and customer support teams to deliver features, solve complex technical problems, and validate innovative solutions.

Provides advanced technical support for ZoomInfo products in a B2B software environment. Diagnoses API, integration, CRM synchronization, data quality, browser, and network issues; manages complex cases through resolution; and collaborates with Product and Engineering teams. Develops troubleshooting documentation, playbooks, training materials, and process improvements while mentoring junior staff and surfacing customer feedback. Supports product releases, beta testing, enablement, and collaboration across Customer Success and Sales.

Provides technical support for customer integrations, troubleshoots incidents, manages engineering escalations, documents best practices, and educates customers on third-party products. The role captures customer feedback, identifies renewal risks and upsell opportunities, and helps drive product adoption and satisfaction. Responsibilities include investigating and replicating issues, communicating technical concepts to varied audiences, and supporting customers across CRM, marketing automation, and sales acceleration platforms.

Build and own production data pipelines, dbt models, semantic layers, and supporting infrastructure across Snowflake, BigQuery, Airflow, Fivetran, Databricks, AWS, and GCP. Partner with stakeholders across business functions to scope requirements, resolve data quality issues, monitor SLAs, support incident response, and apply data governance practices. The role requires autonomous delivery, strong communication, production-grade Python and SQL, and contributions to engineering standards, CI/CD, testing, and documentation.

Provides strategic and day-to-day labor and employment counsel across the company’s U.S. workforce while coordinating international matters in the UK, Ireland, India, Canada, and Israel. Advises HR and executives on employee relations, performance management, accommodations, leave, terminations, policies, agreements, compliance, and litigation. Manages outside counsel and builds scalable employment processes, playbooks, and decision frameworks in a fast-paced technology company.

Architects and standardizes cloud infrastructure for data platforms on GCP, including Kubernetes, networking, Terraform, GitOps, CI/CD, observability, performance, cost, security, and disaster recovery. Evaluates emerging data technologies, runs prototypes, guides managed-service connectivity, supports governance and consolidation, and enables engineering teams through architecture reviews, workshops, reference implementations, and documented standards.