Job Description
About the Company
Our client is redefining how enterprises harness the power of generative AI. Their platform enables business and data analysts to build intelligent agents that automate insights, reporting, and operational workflows across the organization. They're helping enterprises move from static dashboards to dynamic, action-driven intelligence. With a focus on security, scalability, and real-world business impact, this company is trusted by global organizations to deliver next-generation analytics and automation through AI.
About the Role
As Engineering Manager, you will lead a high-impact team building the core SaaS product and AI agent platform. You'll combine hands-on technical leadership, people management, product thinking, and operational excellence. You'll partner with product, data science, DevOps, and go-to-market teams to drive scalable, secure, enterprise-grade features. Your mission is to ensure the product is robust, extensible, performant, and supports customers AI-driven workflows.
Key Responsibilities
- Lead and mentor a team of engineers (frontend, backend, data/AI infrastructure), setting technical direction, reviewing designs and code, and driving best practices.
- Define and execute engineering roadmaps aligned with product strategy and business goals, particularly for B2B enterprise SaaS, security/compliance, and AI agent workflows.
- Collaborate closely with leadership and cross-functional teams to deliver features from concept through production with a focus on quality, reliability, performance, and maintainability.
- Drive architectural decisions around AI/ML pipelines, data integration, multi-tenant SaaS infrastructure, security, and scalability.
- Establish and monitor key metrics for engineering delivery, quality (e.g., test coverage, incident rates), performance, and team health.
- Build a culture of strong engineering practices including CI/CD, code reviews, test automation, monitoring/observability, and incident postmortems.
- Foster career growth of engineers through coaching, feedback, and development planning.
- Ensure the product complies with enterprise expectations for governance, auditability, transparency, and accuracy.
- Stay current with emerging AI/ML trends, SaaS best practices, and enterprise customer requirements, and bring in innovations where applicable.
Minimum Qualifications
- 8+ years of software engineering experience, including at least 23 years in a people management role.
- Proven experience building B2B SaaS products (preferably enterprise scale) including multi-tenant architecture, security, compliance, integrations, and scalability.
- Background working in an AI or ML product context such as inference pipelines, model deployment, feedback loops, or agent/automation frameworks.
- Strong technical foundation across backend services, API design, cloud infrastructure (AWS/Azure/GCP), data systems, and scalable architecture.
- Excellent leadership and communication skills with experience collaborating cross-functionally and influencing technical and product decisions.
- Experience implementing engineering processes such as release management, testing, monitoring, and metrics-driven improvement.
- Comfort working in a fast-paced startup environment with a hands-on approach and adaptability.
Preferred Qualifications
- Experience working directly with enterprise customers (Large Enterprise / Fortune 500) on complex workflows, compliance, and data governance.
- Experience building no-code or low-code platforms.
- Familiarity with generative AI, large language models, agent architectures, or workflow automation.
- Understanding of data connectors, ETL pipelines, semantic modeling, knowledge graphs, or similar.
- Experience managing distributed teams and cultivating engineering culture across geographies.
What You'll Get
- Opportunity to lead engineering at a rapidly scaling AI enterprise SaaS startup headquartered in the Bay Area, working at the intersection of analytics, automation, and AI.
- A chance to influence product roadmap, architecture, and company direction from early stages.
- Collaborative, high-energy environment where technical leadership and impact are recognized and rewarded.
- Competitive compensation reflecting startup growth potential.
- The ability to build trusted, enterprise-grade products that solve real business problems and deliver measurable impact.
