Remote Lead AI Engineer Jobs
Remote Lead AI Engineer jobs are open across the U.S. at remote-first firms and distributed engineering teams, with strong demand in technology, finance, and healthcare. Companies hiring remotely right now include LawnStarter, EPAM Systems, and Target. See the openings below and apply to the ones that match your experience.
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Showing 5 of 144+ Remote Lead AI Engineer jobs
About LawnStarter
LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $750M in bookings. We're expanding beyond lawn care to become the one-stop shop for home services: three brands (LawnStarter, Lawn Love, Home Gnome), one shared platform.
About Product at LawnStarter
Our BHAG: 1+ job per household, every year. Getting there means winning on four fronts at once: more customers, more Pros, excellent service for both sides, and an AI-run company that moves faster than its size should allow.
About AI Agents at LawnStarter
Our mission: power every AI experience. For homeowners and for Pros (the lawn care providers on our marketplace), conversational AI can do far more than answer questions. It can skip a service, reschedule a visit, or book a new one mid-conversation, even when the customer's own AI agent is the one talking. And it doesn't have to live only in a chat window: we're bringing agentic experiences into the workflows homeowners and Pros already use, so the product does the work for them wherever they are. You'll decide what that looks like for both sides, then ship it.
The Role
This is LawnStarter's first core AI PM role. You'll own our conversational AI and agent experiences for consumers and Pros: the chat, the actions it takes, the moment it hands off to a person, and how outside AI agents work with us. Beyond chat, you'll bring agentic experiences into existing consumer and Pro workflows, so AI takes action inside the product rather than alongside it.
As Lead PM, you're an individual contributor with Lead-level scope, reporting to the Sr. Director of Product. The AI experiences you power will often sit inside surfaces other PMs own, so you'll share goals with the Customer Experience lead, the First Service Experience lead, and the Pro Experience PM, and build with engineering, applied science, design, data, customer service, and operations.
What makes this role different:
- Fast, and at the center. Within a year, we expect AI to shape a meaningful share of how homeowners and Pros experience LawnStarter, and you’ll be at the center of making that happen. This role moves fast and rewards people who ship.
- You're the first. The evals, the guardrails, and the bar for "ready to ship" are yours to set.
- The AI takes real actions. It reschedules and skips services on a live marketplace. No sandbox.
- Two sides, one conversation. Everything you ship serves homeowners, Pros, or both, and an action for one changes the other's day.
What You'll Own
- The AI roadmap: Where consumer AI and Pro AI go next, and the order we build it in.
- Customer AI chat: Answering homeowners' questions and completing tasks, like skipping or rescheduling a service.
- AI chat in the Pros App: The AI experience Pros get inside the app they work from.
- Agents inside existing workflows: AI that acts within the consumer and Pro flows people already use, not just in a chat window.
- Customer-to-Pro messaging: How homeowners and Pros talk to each other.
- The handoff to human support: When the bot passes a conversation to a support agent.
- Outside AI agents: Letting a customer's own agent, such as ChatGPT or Claude, work with us on their behalf.
Problems to Solve
From answering questions to solving problems.
A chatbot that explains how to reschedule is useful. One that understands what the customer or Pro actually needs, recommends the right thing, and then does it for them is a different product, and a riskier one. Sometimes the best answer isn’t the action they asked for: a skip might be better as a reschedule, or a one-time booking better as a plan. You’ll decide which actions the AI takes on its own, which need confirmation, and what happens when it gets one wrong.
Knowing when to hand off, and doing it well.
Some conversations belong with a person. Which ones? And can the bot tell before the customer gets frustrated? When the handoff comes, the support agent should pick up with full context so the customer doesn't repeat themselves.
When the customer's agent is the one asking.
Sometimes the one talking to LawnStarter won't be a homeowner. It'll be their own AI agent, such as ChatGPT, asking about a service, booking one, or changing it. You'll work out what we let an outside agent do and how the customer stays in control.
Evals and guardrails for two audiences.
A good answer for a homeowner isn't a good answer for a Pro. You'll build the evals that tell us when an AI experience is good enough to ship and when its quality slips, plus the guardrails that keep it safe once it's live.
What Success Looks Like (Year 1)
- AI shaping the experience: AI experiences live for consumers and Pros, and shaping a meaningful share of how both sides interact with LawnStarter, measured by:
- Share of conversations resolved by AI without a human (resolution or containment rate)
- CSAT on AI conversations, for homeowners and Pros
- Action accuracy: errors on reschedules, skips, and bookings stay below a set bar
- Pros get more done because of AI: Pros spend less time on admin and coordination, and say AI makes them more productive.
- More customers stay because AI makes service better: Consumer and Pro retention rises, driven by AI that resolves problems faster and improves the service experience.
Requirements
Who You Are
Experience: 6+ years of product management, including at least 3 years launching AI products to customers (internal or external).
An AI builder who has shipped to real users. You've put AI products in front of real end users, whether in B2C, B2B, or B2B2C, and at least one was a chatbot or conversational AI running in production. You read transcripts to find where conversations break. If your AI work stopped at demos, prototypes, or a thin prompt wrapper that never met a real user, this isn't your role.
The owner of quality. You write evals yourself. You know when an AI experience is good enough to ship, and when its quality starts to slip. Would you rather someone else define what "good" means? Then you'll struggle here.
Fluent in agents and tool use. You understand what changes when an agent stops producing text and starts calling actions on real systems, and you design for the ways that goes wrong. PMs who treat AI as a feature bolted onto the side won't last here.
A strategist who prioritizes with data. You set priorities, say no with reasons, and back each call with evidence. If your roadmaps run on instinct alone, this is unlikely to be a good fit.
A systems thinker. You see a product change as one part of a larger system and think through its second- and third-order effects before you ship. Here, that system is a marketplace: a change for customers almost always touches Pros, pricing, and operations too. You plan for those effects in the spec, not after launch. Marketplace experience helps, but what matters most is that you instinctively ask, "What else does this change?" If you'd rather ship your piece and let other teams deal with what it changes, this isn't your role.
This Role Is NOT
- A people-management role. You're an individual contributor with no direct reports.
- A research or ML-platform seat. If your AI career has been research or platform work that never reached end users, this isn't the fit.
- For AI skeptics. If you see AI as an add-on rather than the product, you'll fight the job daily.
- A strategy-only seat. You'll write the evals and read the transcripts. Setting direction from a distance won't work here.
- A role with foundations already built. You'll build the evals, the guardrails, and how we decide an AI experience is ready, not inherit them. We're also lean and frugal, on a partly legacy stack.
-
Low-stakes. AI that reschedules or skips a service fails in front of customers and Pros, so the safety bar is high. And since your work lives inside surfaces other PMs own, you'll lead through influence.
Bachelor’s degree in business, analytics, engineering, design, or a related field, or equivalent practical experience, plus 6+ years of product management experience on consumer-facing products.
Benefits
- Equity: AI is how LawnStarter plans to move faster than its size, and this role decides how that shows up for customers and Pros. Equity means you share in what that builds.
- Base salary: $170,000 to $225,000
- Healthcare: Medical, dental, and vision
- Location: Fully remote (US). Evals, transcripts, and failure cases reward deep focus, and remote work protects it.
- PTO: Flexible. We focus on results. Take what you need.
LawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment.
About LawnStarter
LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $750M in bookings. We're expanding beyond lawn care to become the one-stop shop for home services: three brands (LawnStarter, Lawn Love, Home Gnome), one shared platform.
About Product at LawnStarter
Our BHAG: 1+ job per household, every year. Getting there means winning on four fronts at once: more customers, more Pros, excellent service for both sides, and an AI-run company that moves faster than its size should allow.
About AI Agents at LawnStarter
Our mission: power every AI experience. For homeowners and for Pros (the lawn care providers on our marketplace), conversational AI can do far more than answer questions. It can skip a service, reschedule a visit, or book a new one mid-conversation, even when the customer's own AI agent is the one talking. And it doesn't have to live only in a chat window: we're bringing agentic experiences into the workflows homeowners and Pros already use, so the product does the work for them wherever they are. You'll decide what that looks like for both sides, then ship it.
The Role
This is LawnStarter's first core AI PM role. You'll own our conversational AI and agent experiences for consumers and Pros: the chat, the actions it takes, the moment it hands off to a person, and how outside AI agents work with us. Beyond chat, you'll bring agentic experiences into existing consumer and Pro workflows, so AI takes action inside the product rather than alongside it.
As Lead PM, you're an individual contributor with Lead-level scope, reporting to the Sr. Director of Product. The AI experiences you power will often sit inside surfaces other PMs own, so you'll share goals with the Customer Experience lead, the First Service Experience lead, and the Pro Experience PM, and build with engineering, applied science, design, data, customer service, and operations.
What makes this role different:
- Fast, and at the center. Within a year, we expect AI to shape a meaningful share of how homeowners and Pros experience LawnStarter, and you’ll be at the center of making that happen. This role moves fast and rewards people who ship.
- You're the first. The evals, the guardrails, and the bar for "ready to ship" are yours to set.
- The AI takes real actions. It reschedules and skips services on a live marketplace. No sandbox.
- Two sides, one conversation. Everything you ship serves homeowners, Pros, or both, and an action for one changes the other's day.
What You'll Own
- The AI roadmap: Where consumer AI and Pro AI go next, and the order we build it in.
- Customer AI chat: Answering homeowners' questions and completing tasks, like skipping or rescheduling a service.
- AI chat in the Pros App: The AI experience Pros get inside the app they work from.
- Agents inside existing workflows: AI that acts within the consumer and Pro flows people already use, not just in a chat window.
- Customer-to-Pro messaging: How homeowners and Pros talk to each other.
- The handoff to human support: When the bot passes a conversation to a support agent.
- Outside AI agents: Letting a customer's own agent, such as ChatGPT or Claude, work with us on their behalf.
Problems to Solve
From answering questions to solving problems.
A chatbot that explains how to reschedule is useful. One that understands what the customer or Pro actually needs, recommends the right thing, and then does it for them is a different product, and a riskier one. Sometimes the best answer isn’t the action they asked for: a skip might be better as a reschedule, or a one-time booking better as a plan. You’ll decide which actions the AI takes on its own, which need confirmation, and what happens when it gets one wrong.
Knowing when to hand off, and doing it well.
Some conversations belong with a person. Which ones? And can the bot tell before the customer gets frustrated? When the handoff comes, the support agent should pick up with full context so the customer doesn't repeat themselves.
When the customer's agent is the one asking.
Sometimes the one talking to LawnStarter won't be a homeowner. It'll be their own AI agent, such as ChatGPT, asking about a service, booking one, or changing it. You'll work out what we let an outside agent do and how the customer stays in control.
Evals and guardrails for two audiences.
A good answer for a homeowner isn't a good answer for a Pro. You'll build the evals that tell us when an AI experience is good enough to ship and when its quality slips, plus the guardrails that keep it safe once it's live.
What Success Looks Like (Year 1)
- AI shaping the experience: AI experiences live for consumers and Pros, and shaping a meaningful share of how both sides interact with LawnStarter, measured by:
- Share of conversations resolved by AI without a human (resolution or containment rate)
- CSAT on AI conversations, for homeowners and Pros
- Action accuracy: errors on reschedules, skips, and bookings stay below a set bar
- Pros get more done because of AI: Pros spend less time on admin and coordination, and say AI makes them more productive.
- More customers stay because AI makes service better: Consumer and Pro retention rises, driven by AI that resolves problems faster and improves the service experience.
Requirements
Who You Are
Experience: 6+ years of product management, including at least 3 years launching AI products to customers (internal or external).
An AI builder who has shipped to real users. You've put AI products in front of real end users, whether in B2C, B2B, or B2B2C, and at least one was a chatbot or conversational AI running in production. You read transcripts to find where conversations break. If your AI work stopped at demos, prototypes, or a thin prompt wrapper that never met a real user, this isn't your role.
The owner of quality. You write evals yourself. You know when an AI experience is good enough to ship, and when its quality starts to slip. Would you rather someone else define what "good" means? Then you'll struggle here.
Fluent in agents and tool use. You understand what changes when an agent stops producing text and starts calling actions on real systems, and you design for the ways that goes wrong. PMs who treat AI as a feature bolted onto the side won't last here.
A strategist who prioritizes with data. You set priorities, say no with reasons, and back each call with evidence. If your roadmaps run on instinct alone, this is unlikely to be a good fit.
A systems thinker. You see a product change as one part of a larger system and think through its second- and third-order effects before you ship. Here, that system is a marketplace: a change for customers almost always touches Pros, pricing, and operations too. You plan for those effects in the spec, not after launch. Marketplace experience helps, but what matters most is that you instinctively ask, "What else does this change?" If you'd rather ship your piece and let other teams deal with what it changes, this isn't your role.
This Role Is NOT
- A people-management role. You're an individual contributor with no direct reports.
- A research or ML-platform seat. If your AI career has been research or platform work that never reached end users, this isn't the fit.
- For AI skeptics. If you see AI as an add-on rather than the product, you'll fight the job daily.
- A strategy-only seat. You'll write the evals and read the transcripts. Setting direction from a distance won't work here.
- A role with foundations already built. You'll build the evals, the guardrails, and how we decide an AI experience is ready, not inherit them. We're also lean and frugal, on a partly legacy stack.
-
Low-stakes. AI that reschedules or skips a service fails in front of customers and Pros, so the safety bar is high. And since your work lives inside surfaces other PMs own, you'll lead through influence.
Bachelor’s degree in business, analytics, engineering, design, or a related field, or equivalent practical experience, plus 6+ years of product management experience on consumer-facing products.
Benefits
- Equity: AI is how LawnStarter plans to move faster than its size, and this role decides how that shows up for customers and Pros. Equity means you share in what that builds.
- Base salary: $170,000 to $225,000
- Healthcare: Medical, dental, and vision
- Location: Fully remote (US). Evals, transcripts, and failure cases reward deep focus, and remote work protects it.
- PTO: Flexible. We focus on results. Take what you need.
LawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment.
See All 144+ Remote Lead AI Engineer Jobs
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Find Remote Lead AI Engineer JobsRemote Lead AI Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Consulting & Professional Services
- Education
- Manufacturing
- Insurance
What Employers Look For
The qualifications that appear most often in remote lead AI engineer jobs.
- Five or more years of machine learning engineering or applied AI experience
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience deploying and monitoring production ML systems at scale
- Familiarity with MLOps tooling, model versioning, and CI/CD pipelines for models
- Strong understanding of large language models, fine-tuning, and prompt engineering
- Bachelor's or master's degree in computer science, machine learning, or a related technical field
Tips for Your Remote Lead AI Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote lead ai engineer openings from across the U.S. in one place, so you can find roles that match your stack and seniority and apply directly. Remote postings at well-known companies fill fast, so check new listings frequently.
Show async leadership in your portfolio
Remote employers want proof you can lead without a whiteboard. Document your AI project decisions in written design docs or public GitHub READMEs that show how you scoped problems, chose architectures, and resolved tradeoffs without real-time back-and-forth.
Highlight distributed team experience upfront
If you've led model development or coordinated with cross-functional partners across time zones, name that explicitly in your summary and cover letter. Remote hiring managers screen for candidates who've already proven they can unblock others asynchronously.
Prepare for remote-first technical interviews
Remote lead ai engineer interviews often include system design sessions over shared documents and async take-home assessments rather than on-site whiteboarding. Practice explaining your architectural decisions in writing and get comfortable presenting model evaluation results clearly in video format.
Remote Lead AI Engineer Jobs: Frequently Asked Questions
How do I get a remote lead ai engineer job?
Target remote-first companies and distributed product teams, since they build workflows around async collaboration and expect lead ai engineers to operate independently from day one. Remote employers screen for strong written communication, demonstrated ownership of model development or deployment pipelines, and experience leading cross-functional work without in-person oversight. A portfolio showing end-to-end AI projects, plus clear written case studies, gives you a concrete edge.
Which companies hire remote lead ai engineers?
Remote lead ai engineer roles are posted by LawnStarter, EPAM Systems, and Target and others right now, based on current remote listings on Migrate Mate as of November 2026. These include remote-first technology companies, distributed fintech and healthtech teams, and enterprise software firms that have built fully remote engineering organizations.
Can you get a remote lead ai engineer job with no experience?
Yes, but remote lead ai engineer roles are harder to land without experience because you're expected to self-direct and unblock others with minimal supervision. Your best entry path is building public projects on GitHub, contributing to open-source AI frameworks, and completing recognized applied AI courses. Remote-first startups and research-adjacent teams are more likely to take a chance on a candidate who demonstrates strong async communication and initiative through their work.
Do you need a degree for remote lead ai engineer jobs?
Not always. Many remote employers care more about what you've shipped than where you studied, especially at the lead level where your ability to architect systems and guide teams matters most. A strong public portfolio, production-grade project experience, and proficiency in relevant frameworks like PyTorch, TensorFlow, or cloud ML platforms can carry significant weight alongside or instead of a formal degree.
Which industries hire the most remote lead ai engineers?
The sectors hiring the most remote lead ai engineers are Technology & Software, Consulting & Professional Services, and Education, based on current remote listings on Migrate Mate as of November 2026. These industries rely on distributed engineering teams that need experienced AI leads who can drive model strategy and delivery without being physically co-located.
See All 144+ Remote Lead AI Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Lead AI Engineer Jobs