Principal Software Engineer

About this role

Vestmark is building the AI-native future of wealth management technology. We are looking for a Principal Engineer who thinks in systems, cares about business outcomes, and has the technical depth to define how AI-native software gets built at scale. If you have a clear point of view on where software engineering is going and want to do the work that proves it, this role is for you.

We set goals as outcomes. The approach is yours to determine. Your decisions will compound over time, measured in workflows eliminated, costs structurally reduced, and capabilities that make every subsequent project faster and cheaper to deliver.

Vestmark is a leading provider of wealth management solutions and services that enable financial advisors and institutions to efficiently manage and trade their clients' portfolios using an innovative SaaS ecosystem. With over $1.5 trillion in assets and 3.5+ million accounts, we are a trusted partner to some of the largest and most respected players across the wealth management industry.

What You'll Do

Design & Build Agentic Systems

• Architect and deliver agentic systems that implement sense → think → act loops: systems that plan, execute, evaluate, and iterate toward outcomes

• Drive the engineering organization beyond prompt-response patterns to multi-step,autonomous workflows that solve real business problems at scale

• Engineer AI-driven workflows where AI takes action, produces measurable output, and improves through iteration and feedback

Set Standards for AI-Native Development

• Define how engineers use AI-assisted development tools, including code generation, prompt engineering, workflow orchestration, and agentic frameworks, as a team-wide engineering discipline rather than individual productivity shortcuts

• Establish and evolve standards for AI-native systems: how they handle nondeterminism, manage state across multi-step processes, maintain observability, and control inference cost and latency

• Define testing and validation approaches for adaptive systems where behavior is not fully deterministic; hold the quality bar for production AI systems across reliability, latency, and correctness

• Serve as the engineering organization's authority on AI-native development practices and drive their adoption across teams

Build Reusable Foundations

• Design and deliver frameworks, integration patterns, and technical capabilities that reduce the cost of building every subsequent solution; the next project should be faster and cheaper because of what you built today

• Apply the principle "fix the process, don't automate the broken one" as a design mandate: identify root causes and address them, not symptoms

• Remain a hands-on practitioner: write clean, testable, maintainable code and hold the team to that standard through rigorous code review

Lead & Grow the Organization

• Collaborate across engineering, product, and operations to share what's working, surface what isn't, and help AI-native practices take hold organically

• Contribute to how Vestmark thinks about building AI-native software, through design reviews, architecture discussions, and hands-on collaboration that raises the whole team's game

• Share what you know freely, whether that's pairing on a hard problem, reviewing a design, or helping a teammate get more out of their AI tooling

• Contribute to the growth and development of our core values: We Before Me, Positive Energy, Knowledge Explorer, and Own It

What We're Looking For

Core Engineering Excellence

• Demonstrated expertise building and delivering complex, production-grade software systems: platforms and frameworks that other teams depend on at scale

• Strong fundamentals across the full engineering lifecycle: architecture, design, development, testing, deployment, and operations

• Comfort designing systems where behavior is non-deterministic and may evolve over time, as a core competency

• Experience with AWS or equivalent cloud-native environments, CI/CD pipelines, and modern deployment patterns

Agentic Engineering & AI Expertise

• Proven, hands-on experience building agentic systems: multi-step, autonomous workflows where AI plans, reasons, acts, and iterates in production environments

• Deep practical knowledge of LLM integration: context management, tool use, orchestration, and state management across multi-step processes

• AI-assisted development tools are a consistent, intentional part of your daily engineering practice

• A clear, defensible point of view on how AI is reshaping software engineering and where it is heading, backed by a track record of delivery

• Understanding of how AI systems interact with data, services, external tools, and real-world operational constraints

• Awareness of the trade-offs unique to AI-native systems, including cost of inference, latency, observability, and reliability, and the judgment to navigate them in production

• Experience designing feedback loops where systems improve through usage, data, and iteration

Independence & Technical Leadership

• Track record of setting technical direction that others have adopted: patterns, methodologies, or architectural decisions that outlasted individual projects and spread across teams

• Ability to engage with ambiguous, real-world business problems: understand the process, identify the waste, and determine the right solution before writing a line of code

• You have built deep expertise through independent study, experimentation, and delivery. Formal training programs in agentic AI engineering are still nascent; you have not waited for them.

What Will Help You Stand Out

• Hands-on experience delivering at least one production agentic system where AI orchestrates multi-step workflows with real autonomy and demonstrable business impact, and the engineering depth to build more

• Experience building platform or framework-level tooling consumed by other engineering teams at scale

• Background in financial services technology, parti

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