Jobs at WorkWave

Owns cloud security across AWS, Azure, and GCP by establishing secure landing zones, guardrails, IAM, container security, vulnerability management, detection, compliance controls, secrets governance, CI/CD security, and incident readiness. The role partners closely with Engineering, DevOps, Security Operations, and GRC teams, automates secure cloud patterns and remediation, manages security tooling, develops metrics and playbooks, and mentors engineers.

Deliver SaaS implementations and integrations by managing data migration, mapping, configuration support, integration validation, UAT, project governance, risk tracking, client training, and go-live readiness. Collaborate with implementation leads, Sales, and Customer Success to ensure successful onboarding, adoption, stakeholder alignment, and timely escalation of delivery or commercial opportunities.

The Mid Market Account Executive will sell WorkWave’s SaaS field service management platform to large service businesses. Responsibilities include prospecting, executive-level discovery, solution selling, product demonstrations with Sales Engineers, managing complex multi-stakeholder sales cycles, building a multi-million-dollar pipeline, and closing strategic contracts. The role requires strong business acumen, relationship-building, disciplined execution, and at least five years of successful SaaS solutions sales experience with a record of exceeding revenue targets.

Manage and expand mid-market SaaS accounts by building executive relationships, conducting QBRs, identifying whitespace opportunities, delivering tailored demonstrations, and managing the full expansion sales cycle. Responsibilities include forecasting, CRM hygiene, ARR quota attainment, negotiation, deal closure, and cross-functional collaboration with customer success, product, and sales engineering teams. Travel up to 25% is required for client meetings and conferences.

Leads architecture for enterprise SaaS platforms across modernization, cloud services, integrations, distributed systems, data platforms, and production AI agents. Designs reference implementations, technical roadmaps, AWS infrastructure, multi-tenant architectures, and event-driven services. Partners with enterprise customers, conducts technical discovery and prototypes, drives engineering standards and security-by-design, and mentors engineers. Requires 8+ years of software engineering experience, including 4+ years leading enterprise-scale distributed platforms.

Build and operate production AI agents and tools on Amazon Bedrock and AgentCore. Own agent quality, retrieval, multi-step workflows, MCP endpoints, evaluation harnesses, regression gates, observability, latency, cost, and runtime guardrails. Measure groundedness, adoption, task success, and customer impact while partnering with Product and engineering teams to improve data and infrastructure. Requires strong Python, AWS, agent engineering, retrieval, evaluation, SQL, product judgment, and cross-functional communication skills.

Own the end-to-end delivery of applied machine learning products, from framing customer problems and building data pipelines to deploying, monitoring, and measuring model impact. Develop models for operational data using Python, SQL, dbt, Snowflake, and AWS; define evaluation and drift monitoring; conduct A/B tests or causal analyses; and partner with product and engineering teams to embed ML into customer workflows.

Manage global SaaS implementation projects from scoping and statements of work through planning, execution, risk mitigation, stakeholder communication, financial control, and closure. The role oversees enterprise and SMB deployments, protects project margins, coordinates international teams, maintains audit-ready documentation, and uses AI and automation to improve efficiency. Domestic travel of up to 25% is required for client meetings and project reviews.

Own the vision, roadmap, and delivery of customer-facing AI, predictive analytics, and SaaS data products. Partner with strategic clients, UX, data science, engineering, sales, and marketing to translate business needs into technical requirements, validate product hypotheses, and launch features that drive adoption, retention, and revenue expansion. Use SQL and data visualization tools to analyze data, communicate insights, and shape intuitive product experiences.

Own the full SMB sales cycle for Pest and Lawn service businesses, from prospecting and inbound lead response through discovery, online demos, proof of concept, negotiation, forecasting, and closing. The role requires maintaining a predictable pipeline, meeting weekly KPIs and quota, using Salesforce, SalesLoft, and 6Sense, and building consultative relationships with small-business stakeholders.