Top Tech Jobs & Startup Jobs

Lead architecture, roadmap, and implementation for Veza’s scalable Access Graph data platform. Solve complex distributed-systems and graph-database challenges, establish engineering standards, improve reliability and performance, and deliver backend services in Go. Drive cross-team planning, technical decisions, design reviews, and stakeholder alignment while mentoring engineers and team leads. Ensure high standards for correctness, testing, documentation, support, rollback safety, and responsible use of AI-assisted engineering tools.

Lead adoption, implementation, deployment, and configuration of the Armis platform for platinum-level customers. Advise technical and executive stakeholders on security use cases, platform utilization, and value realization. Build trusted customer relationships, advocate internally, coordinate cross-functional teams, support integrations, and identify growth opportunities. Serve as a technical subject matter expert while partnering with Product, Engineering, Support, Sales, and Training teams. Travel may be required up to 20–25% per quarter.

Drive revenue for ServiceNow Finance, Procurement, and Legal Workflow solutions through enterprise sales partnerships, pipeline development, executive discovery, account strategy, product demonstrations, technical consultation, and complex deal closure. The role requires translating AI and workflow automation capabilities into business value, building executive relationships, and collaborating effectively in a matrixed environment.

Own technical relationships with strategic enterprise customers throughout Moveworks implementations. Design AI agent solutions, enterprise integrations, workflows, and automations using APIs, iPaaS tools, cloud functions, and scripting. Advise customers on agentic AI roadmaps, coordinate cross-functional delivery, develop reusable capabilities, and mentor engineers. The role combines solution architecture, hands-on implementation, technical consulting, executive communication, and up to 25% travel.

Drives enterprise sales of ServiceNow Finance, Procurement, and Legal Workflow solutions. Builds pipeline, develops account strategies, leads executive discovery, quantifies AI value, demonstrates solutions, answers technical questions, and closes complex SaaS deals. Partners with enterprise sales teams and cross-functional stakeholders while maintaining executive relationships and staying current on AI and workflow automation trends.

Leads ServiceNow’s Measurement & Modeling team, defining product measurement strategies, metrics, and models linking user experience to business outcomes. Oversees AI-enabled research, analytics, data science, engineering, and measurement product delivery. Partners with product, design, research, and data leaders to translate findings into strategic decisions, builds a high-performing global team, develops talent, and advances innovative measurement practices.

Leads ServiceNow’s enterprise portfolio naming strategy, governance, operating model, tooling, and organizational capability. Partners with Product, Marketing, Brand, Design, Legal, Pricing, and executives to improve portfolio clarity, naming architecture, decision velocity, and commercial impact. Builds scalable workflows, metrics, automation, and governance while leading a high-performing team and influencing senior stakeholders across complex enterprise technology portfolios.

Advises federal customers on ServiceNow platform strategy, architecture, governance, integrations, data design, security, and platform health. Builds executive relationships, translates business objectives into technical roadmaps and architectural blueprints, guides partners and consulting organizations, and manages implementation decision points across large enterprise programs. The role promotes ServiceNow leading practices, supports digital transformation, contributes thought leadership, and advises customers without performing platform configuration. Travel may reach 50%.

Architect and build large-scale distributed data platform components, ingestion pipelines, and Data Lake solutions. Lead complex technical initiatives, develop reusable libraries and frameworks, optimize Java and JVM performance, and ensure reliable, scalable operations. Collaborate across teams, establish engineering best practices, evaluate emerging technologies, and troubleshoot production issues across distributed systems using Kafka, Apache Iceberg, Apache Spark, and related data technologies.

Architect and build large-scale distributed systems, data ingestion pipelines, and Data Lake platforms. Develop scalable, fault-tolerant components using Java, Kafka, Apache Iceberg, and Apache Spark; optimize JVM performance; create reusable frameworks; troubleshoot production issues; and provide technical leadership across complex engineering initiatives.