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About This Role
Vestwell is the financial technology company powering the new savings economy. Our platform redefines how people save for the critical aspects of life across retirement, education, and healthcare savings needs. Today, Vestwell enables over 350,000 businesses and over 2M active savers, with over $50B in assets saved across all 50 states. Vestwell's platform serves a diverse clientele, including financial advisers, employers, third\-party administrators, financial institutions, payroll providers, government agencies, and individual savers.
To learn more, visit vestwell.com
Who Are We Looking For?
The Engineering team is seeking an experienced Engineering Manager to lead our AI Engineering organization. This leader will be responsible for building and scaling the engineering team that delivers AI\-powered products and enterprise capabilities. You will combine strong technical leadership with exceptional people management, partnering closely with Product, Design, Data, and business leaders to define strategy, execute against ambitious roadmaps, and deliver reliable, production\-grade AI solutions.
The ideal candidate has a proven track record of leading high\-performing engineering teams while remaining technically credible in modern AI and software engineering. You know how to balance execution with long\-term architecture, mentor engineers, raise the engineering bar, and build systems that scale.
You're a great fit if you enjoy developing people as much as technology, can navigate ambiguity, and are passionate about delivering AI solutions that create measurable business value.
What Will You Be Doing?
Your responsibilities will include, but are not limited to:
- Lead, mentor, and grow a team of AI software engineers, fostering a culture of technical excellence, ownership, and continuous learning.
- Drive engineering execution by establishing priorities, managing delivery, and ensuring predictable, high\-quality outcomes.
- Define the technical architecture and engineering direction for AI platforms, services, and enterprise applications.
- Partner with Product, Design, Data Science, Security, and business stakeholders to translate business objectives into scalable technical solutions.
- Architect, build, and oversee the delivery of production\-grade AI services with a focus on reliability, scalability, observability, and operational excellence.
- Guide the implementation of modern AI capabilities, including retrieval\-augmented generation (RAG), AI agents, orchestration frameworks, and integrations with leading LLM providers.
- Establish engineering best practices for software development, testing, deployment, code quality, and operational support.
- Remain technically engaged by reviewing architecture, mentoring engineers, and contributing to key technical decisions and complex implementations when appropriate.
- Recruit, coach, and develop engineering talent while helping shape the long\-term growth of the AI Engineering organization.
Requirements
The Necessities
- Bachelor's degree in Computer Science, Engineering, Physics, Mathematics, or a related technical field.
- 8\+ years of professional software engineering experience, including at least 3\+ years leading engineering teams.
- Proven experience building, delivering, and operating production software systems at scale.
- Experience leading engineering teams responsible for AI/ML\-enabled products or platforms.
- Strong hands\-on experience developing production applications in Python.
- Deep understanding of modern AI and machine learning concepts, including large language models (LLMs), retrieval\-augmented generation (RAG), AI agents, and model orchestration frameworks.
- Experience integrating AI services using leading LLM providers and modern AI frameworks such as LangChain, LangGraph, or similar technologies.
- Experience designing cloud\-native applications using AWS, Docker, and modern deployment and CI/CD practices.
- Experience with relational databases (PostgreSQL preferred) and distributed application architectures.
- Strong understanding of software engineering best practices, including testing, observability, security, code review, and operational excellence.
- Demonstrated ability to recruit, mentor, and develop high\-performing engineering teams.
- Excellent communication and collaboration skills with the ability to influence technical and non\-technical stakeholders.
- Experience working in Agile development environments using tools such as GitHub, Jira, and Jenkins (or equivalent).
The Extras
- Experience in financial technology or regulated industries.
- Startup or high\-growth company experience.
- Experience building and scaling AI platforms used across multiple products or business functions.
- Experience leading engineering organizations through rapid growth or organizational change.
Our Culture
We take a modern Agile approach to development, trusting cross\-functional squads to make bottom up decisions in terms of roadmap prioritization, technical choices, and day\-to\-day processes. We want squads to be first class citizens, working as a team to define their roadmap and prioritization, that follows best practices in development, automation testing, deploying, and support.
This role will be based in our New York office, and will be part of Vestwell's hybrid in\-office operation.
The expected base salary range for this position is $195K \- $205K base. This position is eligible to participate in the Company Bonus Pool and is eligible to receive new hire equity in the Company. Please note that salary bands are based on NY and other similar metro areas and may differ based on where the role is ultimately hired.
OUR BENEFITS
We're an innovative, high\-growth company with an exciting future ahead. At Vestwell, we prioritize employee wellbeing through comprehensive health benefits, generous time off, and a dedicated Employee Wellbeing Committee. Our hybrid work model offers flexibility while providing access to our collaborative offices in Midtown Manhattan, Austin, King of Prussia, and Scottsdale. And, of course, as a company focused on helping people save for the future, we offer a competitive 401(k) plan.
OUR PROCESS
Our interview process starts the same for every candidate with 1\-2 introductory conversations to learn more about your background, interests, and what you're looking for, while also giving you the opportunity to learn more about Vestwell and the team. From there, the process varies by role but typically includes a skills or experience\-based assessment, such as a coding interview, portfolio review, or deeper discussion of your relevant experience. Successful candidates then move on to a virtual or in\-person interview panel. Before extending an offer, we complete a reference check with a current or former manager and a peer. Throughout the process, we prioritize transparency, clear communication, and minimizing surprises.
For your awareness you will only receive correspondence from recruiting@vestwell.com any other domain not ending in Vestwell.com is not our Recruitment team.
*Vestwell's* *Privacy Policy.* *Attention California residents: In the course of conducting our business and complying with federal, state, and local government regulations governing such matters as employment, tax, insurance, etc., we must collect Personal Information from you. Should you accept employment with Vestwell you may view our California Privacy Rights Act here:* *Vestwell's California Privacy Rights Policy.*
Salary Context
This $195K-$205K range is above the median for AI Software Engineer roles in our dataset (median: $183K across 194 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Vestwell, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $219,250 based on 424 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($200K) sits 9% below the category median. Disclosed range: $195K to $205K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Vestwell AI Hiring
Vestwell has 1 open AI role right now. They're hiring across AI Software Engineer. Based in New York, NY, US. Compensation range: $205K - $205K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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