Software Engineer

Summary

Vestmark is building the AI-native future of wealth management technology. They are looking for early-career Software Engineers who are serious about AI-assisted development and ready to contribute to systems that matter.

Responsibilities

• 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
• 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
• 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
• 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

Skills

• 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 at least one language, with willingness to use whatever the problem requires
• Understanding of APIs, basic cloud concepts, and modern software delivery practices
• 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
• 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
• 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
• 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
• B.S. in Computer Science or equivalent work experience; M.S. a plus
• 0-3 years of professional software engineering experience; strong internship experience or personal project work considered
• Demonstrated AI tool fluency matters more here than years of experience
• 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, or body of work you can speak to in depth: something you built, something that broke, and what you learned from both

Qualifications

Must Haves

• 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 at least one language, with willingness to use whatever the problem requires
• Understanding of APIs, basic cloud concepts, and modern software delivery practices
• 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
• 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
• 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
• 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
• B.S. in Computer Science or equivalent work experience; M.S. a plus
• 0-3 years of professional software engineering experience; strong internship experience or personal project work considered
• Demonstrated AI tool fluency matters more here than years of experience

Nice to Haves

• 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, or body of work you can speak to in depth: something you built, something that broke, and what you learned from both

Benefits

• Equity-based grants for all new hires
• Company-paid medical premiums of 90%
• A competitive time-off program
• Other variable compensation, if eligible