Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Provides technical presales support by discovering customer requirements, designing Precisely solutions, leading technical discussions, delivering customized demonstrations, and implementing proofs of concept. Builds cloud and AI-driven data solutions using platforms such as Databricks, Snowflake, AWS, Azure, and GCP. Advises customers on data strategies, supports sales teams, influences product positioning, and represents the company at industry events. The role is fully remote in the United States with approximately 30% travel.

Leads architecture and development of scalable Node.js SaaS applications and data products. Responsibilities include designing systems, translating stakeholder needs into technical backlogs, writing user stories, coordinating architecture decisions, supporting product planning, improving business processes, and mentoring engineers. The role also incorporates AI-assisted development, code review agents, LLM APIs, agentic workflows, and generative AI tools.

Own reliability, performance, scalability, and operational standards across on-premises, private-cloud, and AWS environments. Build infrastructure-as-code, deployment automation, monitoring, alerting, and observability tooling; define SLOs, SLIs, error budgets, and readiness standards. Lead incident response, root-cause analysis, disaster-recovery readiness, release coordination, and preventive automation. Mentor engineers, coach teams on operational practices, coordinate on-call coverage, and ensure infrastructure meets security and compliance requirements.

Remote Sales Engineer responsible for technical discovery, product presentations, demonstrations, proof-of-concepts, workshops, and pre-sales training. The role partners with Account Executives, advises customers on SAP, cloud modernization, AI, data quality, and data strategy solutions, and develops custom solutions using platforms such as Databricks, Snowflake, AWS, Azure, and GCP. Requires customer-facing relationship management, generative AI knowledge, cloud-native experience, and approximately 25–30% travel.

Lead FedRAMP certification and compliance programs for cloud and SaaS offerings from planning through continuous monitoring. Coordinate product, security, cloud, engineering, customers, and other stakeholders; manage scope, resources, risks, milestones, deliverables, and action items. Provide technical guidance on federal security requirements, compliance reporting, and solution quality while using AI tools to improve documentation, processes, and regulatory control validation.

Own key FP&A processes including financial reporting, cash forecasting, budgeting, long-range planning, financial modeling, and ad hoc analysis. Partner with cross-functional teams and executives to provide insights, improve processes, automate workflows, and align operational plans with financial goals. The role requires advanced Excel skills and use of AI productivity tools such as Claude and Microsoft Copilot.

Design, architect, develop, test, and support scalable full-stack applications for a data catalog platform. Own features end to end, contribute to technical strategy and roadmaps, ensure operational excellence, collaborate across distributed teams, and mentor engineers. Build multi-tenant systems supporting high data volumes and near-real-time analytics while applying AI-assisted development practices.

Drive enterprise software sales across named Federal, Department of Defense, and aerospace and defense accounts. Develop territory plans, generate pipeline, close new business, expand existing accounts, build executive relationships, manage complex sales cycles, collaborate with marketing and sales engineering, leverage partners, and maintain forecasts in Salesforce CRM. The role is fully remote in the Mid-Atlantic US and requires approximately 25% travel.

Design, architect, develop, test, and support scalable full-stack applications for a high-volume, multi-tenant data platform. Own features from design through delivery, contribute to technical strategy and roadmap development, ensure operational excellence, collaborate across distributed teams, and mentor engineers. Apply cloud-native technologies and AI-assisted development practices while supporting near-real-time analytics and reliable production operations.

Lead delivery and adoption of an AI-enabled PMO across Professional Services: own program end-to-end, identify high-impact AI use cases and ROI, deliver billable client engagements, enable and train teams, govern AI outputs, and run program cadence including backlog, reporting, and stakeholder alignment.