Vestmark Manager, Software Engineering leading a team of up to 12 engineers delivering AI-native wealth management technology. Owns delivery process and invests in team growth and AI fluency.
Responsibilities
Co-own the kanban process with product management: maintain flow, manage WIP, prioritize ruthlessly, and hold the team to delivery commitments
Translate business priorities into clear, sequenced work with defined outcomes and measurable success criteria
Surface blockers and risks early and resolve them; stakeholders should always have an accurate picture of where things stand
Apply the principle “fix the process, don’t automate the broken one”: engage deeply enough with the work to know when the solution is right, not just when it is done
Build & Develop the Team
Recruit, hire, onboard, and develop a team of engineers, including both existing Vestmark engineers and new hires aligned with the AI-native profile we are building toward
Manage performance actively: set clear expectations, provide direct feedback, recognize strong performance, and address underperformance without delay
Integrate engineers from different starting points into a cohesive team with shared standards, mutual accountability, and consistently high output
Invest in each person’s growth, with particular focus on building AI fluency across the team regardless of starting point
Contribute to the growth and development of our core values: We Before Me, Positive Energy, Knowledge Explorer, and Own It
Drive AI-Native Practice
Model AI-native development practices yourself: use AI tools actively in how you plan, communicate, analyze work, and operate as a manager
Qualification
Leadership & People ManagementDirectDelivery OwnershipFluency with kanban-based deliveryBias for actionAI Fluency & Adaptability
Required
Leadership & People Management
Demonstrated experience managing a software engineering team of meaningful size; you have hired, developed, and managed out, and you can speak to each with specificity
Track record of building high-performing teams, including integrating engineers with different skill levels and backgrounds into a cohesive unit
Direct, honest communicator: equally effective giving feedback to an individual engineer and presenting delivery status to senior leadership
You treat performance management as a core competency: you set clear expectations, give direct feedback, and don't let underperformance linger
Delivery Ownership
Proven ability to own end-to-end delivery across multiple concurrent workstreams with genuine accountability for outcomes
Fluency with kanban-based delivery: WIP management, flow metrics, continuous prioritization, and outcome-based planning
Ability to engage with business problems deeply enough to make good sequencing and trade-off decisions, not just manage tasks
Bias for action: you make the call, communicate it clearly, and adjust if you are wrong
AI Fluency & Adaptability
You use AI-assisted development tools and agentic systems regularly and with genuine depth: you have opinions about them, you are actively developing your practice, and you model that standard explicitly for the engineers on your team
