Senior Java Software Engineer

Vestmark, Inc. · Wakefield, MA (Hybrid)

  • Senior
  • Full-time
  • $112,000 – $145,000
  • Posted 2026-09-08
  • Confirmed live on 25 September 2026

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Job description

Vestmark is building the AI-native future of wealth management technology. We are looking for a Senior Java Software Engineer who is serious about AI-assisted development, curious about how software engineering is changing, and ready to do real work on systems that matter. You will not be handed a ticket queue. You will be expected to think, build, and grow quickly in an environment where AI fluency is the baseline, not the aspiration.

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 a purpose-built SaaS ecosystem. With over $2 trillion in assets and 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

Build Agentic Systems

• Contribute to the design and delivery of agentic systems: workflows where AI plans, executes, and iterates toward outcomes rather than simply responding to requests

• Build and ship production-quality solutions as part of a squad working on real efficiency and automation problems with direct business impact

• Participate in the full delivery lifecycle: design discussions, development, testing, deployment, and iteration

Apply AI-Native Development Practices

• Use AI-assisted development tools, including code generation, prompt engineering, and agentic frameworks, as a standard part of your daily workflow from day one

• Learn and apply the team’s standards for building AI-native systems: state management, observability, non-determinism, and inference cost awareness

• Engage with testing and validation approaches specific to adaptive systems where behavior is not fully deterministic

Contribute to Reusable Foundations

• Create clean, testable, maintainable solutions that strengthen the team's shared foundation; treat code quality as a direct contribution to everyone who touches this codebase after you

• Apply the principle “fix the process, don’t automate the broken one”: understand the problem deeply before proposing a solution

• Participate in code reviews as both a reviewer and a recipient; treat both as learning opportunities

Grow & Contribute to the Team

• Engage actively in design reviews and architecture discussions, asking questions and developing your point of view over time

• Take feedback seriously and apply it quickly; growth velocity matters here as much as current skill level

• 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

Engineering Fundamentals

• Solid foundational knowledge of software engineering: data structures, algorithms, system design basics, and how production systems behave under real-world conditions

• Ability to build and deliver working solutions in Java, with willingness to use whatever the problem requires

• Understanding of APIs, basic cloud concepts, and modern software delivery practices

AI Fluency & Curiosity

• Genuine, hands-on familiarity with AI-assisted development tools: you use them regularly, you have opinions about them, and you are actively developing your practice

• Curiosity about agentic systems: how AI can plan, take action, and iterate toward outcomes in multi-step workflows

• Awareness of where AI tooling is heading and a desire to stay current as it evolves rapidly

Problem-Solving Orientation

• Ability to engage with ambiguous problems: ask good questions, break the problem down, and propose a reasonable approach before jumping to a solution

• Comfort working on problems where the full solution isn’t defined upfront

• Attention to the business context of the work: understanding why something matters, not just what needs to be built

Learning Velocity

• Demonstrated ability to learn quickly and independently: you don’t wait to be taught everything

• Receptive to feedback and able to apply it quickly; the expectation is continuous improvement, and you take that seriously

• Evidence of intellectual curiosity beyond coursework: personal projects, open source contributions, self-directed learning in AI or systems engineering

Product Mindset

• You engage with the problem before you engage with the solution; you ask why before you ask how, and you want to understand what you're building and whether it's the right thing to build

• You form a point of view on what you're building and why it matters; you don't treat requirements as fixed inputs but as the starting point for understanding the problem

What Will Help You Stand Out

• Hands-on experience with agentic frameworks, LLM APIs, or workflow orchestration tools, whether through coursework, personal projects, or early professional work

• Experience with AWS or equivalent cloud environments, even at a basic level

• Background or coursework in financial services, mathematics, or quantitative disciplines

• A project, contribution

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