Remote AI Product Engineer Jobs
Remote AI Product Engineer jobs are open across the U.S. in software, healthcare tech, and enterprise AI, at remote-first companies and distributed product teams ranging from early-stage startups to established technology firms. Employers hiring remotely right now include Humana, Cwill, and ServiceNow. Find a role that fits below and apply directly.
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About Positron AI
Positron AI is building next-generation AI inference accelerators designed from the ground up for low-latency, high-throughput large language model inference. Our first-generation ASIC, Asimov, is a cutting-edge accelerator targeting frontier AI workloads, with additional generations already underway.
Role Overview
Positron AI is looking for a Technical Product Manager to own AI inference and software technical product planning end to end. In this role, you will be the person who translates where models and inference systems are heading into concrete, well-scoped requirements for our inference software stack, spanning model coverage, numerics, inference-engine features and modes, serving-stack capabilities, and our managed service.
This is a deeply technical planning role that sits at the intersection of engineering, go-to-market, and the broader inference ecosystem. You will track the model frontier as a discipline, convert that movement into engineering requests before it becomes a customer escalation, and serve as the connective tissue between our engineering organization, our GTM teams, and our ecosystem partners. You will also be expected to use agentic AI daily as a core part of how the planning function operates.
Key Responsibilities
Product Requirements and Roadmap
- Serve as the leader at Positron for all aspects of AI inference and software technical product planning.
- Write requirements for the inference software stack spanning model coverage, numerics, inference-engine features and modes, serving-stack features and modes, and managed-service capabilities.
- Partner with engineering and GTM to build and communicate a clear, defensible roadmap.
- Create scope and feasibility frameworks that convert model and inference-system innovations into tangible engineering requests.
Market and Frontier Tracking
- Keep planning ahead of where models and inference systems are going, tracking the model frontier as a discipline and converting movement into requirements before it surfaces as a customer escalation.
- Work closely with GTM teams to understand customer and market needs and feed them back into the roadmap.
- Create competitive briefings covering inference providers, serving stacks, and adjacent hardware platforms.
- Engage key ecosystem partners, including model labs, open-source runtimes, and serving and orchestration partners, to understand their technology roadmaps.
Lifecycle, Documentation, and Process
- Define and manage the software product lifecycle, including versions and release trains, feature modes, model catalog, and deprecation policy.
- Ensure our software products are well documented for both internal and customer-facing audiences.
- Streamline and automate the product planning process using agentic AI.
Required Qualifications
- 10+ years of experience across ML systems, inference infrastructure, or serving-stack engineering, with direct ownership of performance or architecture trade-offs.
- Deep expertise in transformer internals at the operator level, including attention variants, MoE routing, KV-cache mechanics, and quantization formats along with their hardware implications.
- Hands-on experience with production inference serving at scale, covering multi-tenancy, latency SLAs such as TTFT and TPOT, batching and scheduling, disaggregated serving, KV-cache management, and observability.
- Working fluency in the open-source inference ecosystem, including vLLM and SGLang-class runtimes, kernels, model ingestion, and how models are released, quantized, and adopted in practice.
- Strong performance analysis skills spanning models and systems, including utilization reasoning, tokens per dollar and tokens per watt arithmetic, and benchmark design, with the ability to build and defend the math personally.
- Demonstrated experience in competitive landscaping and analysis of inference providers and serving stacks, gained at a model lab, an inference API provider, or an AI hardware company.
- A proven ability to learn quickly and span the full stack, from model-architecture details up to fleet-scale serving systems, while staying current with the model and inference landscape.
- Excellent communication and interpersonal skills, with comfort navigating uncertainty and driving a process of idea and decision socialization.
- Confidence being the most technically grounded person in a GTM room and the most market-aware person in an engineering room.
- A strong instinct for owning decision history, serving as the documented answer to "why did we choose X," including with executive leadership.
- Daily, hands-on use of agentic AI in real technical work, building and running agent workflows for research, analysis, and requirements drafting, with the judgment to verify and own everything the agents produce.
Preferred Qualifications
- Prior experience at an AI hardware or custom silicon company, with exposure to the realities of bringing a new accelerator platform to market.
- Direct contribution to or close engagement with open-source inference runtimes or serving projects.
- Experience defining and operating a managed inference service, including model catalog and deprecation policy.
- A track record of building internal automation or agentic workflows that measurably improved a planning or research function.
Leveling & Scope
While this role is currently posted at a specific level, we are a growth-oriented organization and are open to hiring at a more senior level for the right candidate. Please note that this job description serves as a focused but generalized overview of the role; specific responsibilities and impact expectations will be tailored to the experience and seniority of the final hire.
Why Join Us?
- You will shape the software roadmap for a purpose-built inference accelerator, working at the layer where model architecture, systems performance, and real customer workloads meet.
- You will have unusually direct influence, defining what gets built across the inference stack and seeing it land in silicon-backed products that compete on performance per dollar and performance per watt.
Compensation & Benefits
The base salary range for this role is $200,000 – $350,000.
Please note that the figures provided represent the base salary range only and do not include other elements of our total compensation package, equity, or comprehensive benefits.
At Positron AI, we value the unique expertise each candidate brings. While the range above reflects our typical expectation for the position, we reserve the flexibility to exceed this range for candidates whose specialized skills, significant experience, or unique qualifications fall outside the standard scope of the role. Final offers are determined based on a variety of factors, including internal equity, and individual impact.
Benefits & Perks
We want you to do your best work and feel confident that you and your family are taken care of. That means comprehensive coverage, real time to rest, and support for your future.
Health and wellness
- Fully company-paid medical, dental, and vision insurance for you and your dependents
- Company-paid life and disability coverage, with voluntary options to add more
- Supplemental hospital, critical illness, and accident coverage available
Time off and flexibility
- Unlimited paid time off, we encourage everyone to truly unplug and recharge
- 13 paid company holidays
- Remote-first culture with a company-provided computer and home office setup
Compensation and future
- Competitive salary and equity
- 401(k) with company matching, eligible from day one
Visa Support
This position is open to candidates currently authorized to work in the U.S. We cannot provide new visa sponsorship for this role but are open to facilitating H-1B visa transfers for eligible candidates.
Equal Opportunity Employer. If you're excited about the role but don't meet every bullet, we'd still love to hear from you.
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Who's Hiring



Top Industries Hiring
- Technology & Software24
- Insurance3
- Consulting & Professional Services3
- Education2
- Cybersecurity2
What Employers Look For
The qualifications that appear most often in remote AI product engineer jobs.
- Bachelor's or master's degree in computer science, engineering, or a related technical field
- Hands-on experience building and shipping features that integrate large language models or ML APIs
- Proficiency in Python and at least one cloud platform such as AWS, Azure, or Google Cloud
- Familiarity with model evaluation, prompt engineering, and retrieval-augmented generation patterns
- Experience with product development lifecycle including requirements, iteration, and cross-functional collaboration
- Understanding of responsible AI principles, model monitoring, and production reliability practices
Tips for Your Remote AI Product Engineer Job Search
Show async communication skills up front
Remote ai product engineer hiring managers screen heavily for written clarity. Include a brief product spec, decision memo, or written case study in your application materials so employers can see how you think and communicate without a live conversation.
Build a portfolio of shipped AI features
Demonstrating that you've taken an AI capability from idea to a working product, even a side project, matters more in remote hiring than credentials alone. Document the problem, your approach, the tools you used, and the outcome in a format you can share quickly.
Apply early to remote roles that fit
Migrate Mate lists remote ai product engineer openings from across the U.S. in one place, so you can find roles that match your experience and apply directly without sifting through unrelated postings.
Prepare for remote-specific interview formats
Many distributed teams use asynchronous take-home exercises instead of live product case interviews. Practice writing concise product briefs and AI feature scopes that can be evaluated without real-time back-and-forth, since that mirrors how you'll actually work if hired.
Remote AI Product Engineer Jobs: Frequently Asked Questions
How do I get a remote ai product engineer job?
Target remote-first companies and distributed product teams that build AI-driven features, since those employers expect async-first work and screen for it explicitly. Remote hiring managers look for strong written communication, the ability to scope and drive AI product decisions independently, and demonstrated fluency with tools like LLMs, product analytics platforms, and cross-functional async workflows. A portfolio showing shipped AI features or measurable product outcomes gives you a clear edge over candidates with equivalent credentials.
Which companies hire remote ai product engineers?
Remote ai product engineer roles are posted by Humana, Cwill, and ServiceNow and others right now, based on current remote listings on Migrate Mate as of August 2026. Remote-first software companies, AI infrastructure firms, and distributed enterprise tech teams account for the largest share of these openings.
Can you get a remote ai product engineer job with no experience?
Yes, but remote entry-level ai product engineer roles are harder to land because employers expect you to operate independently from day one without in-person onboarding or mentorship. The companies most likely to hire entry-level candidates remotely are AI-focused startups that value demonstrated initiative. A portfolio of personal AI projects, open-source contributions, or a completed product sprint can substitute for direct job experience and open doors that a resume alone won't.
Do you need a degree for remote ai product engineer jobs?
Not always. Many remote employers prioritize demonstrated product sense and hands-on AI experience over formal credentials, particularly at startups and remote-first technology companies. What consistently matters is your ability to translate AI capabilities into product decisions, work without close supervision, and communicate clearly in writing. A portfolio of shipped work, certifications in relevant AI or product tooling, and a clear record of results can carry more weight than a degree alone.
Which industries hire the most remote ai product engineers?
Remote ai product engineer roles concentrate in Technology & Software, Insurance, and Consulting & Professional Services, based on current remote listings on Migrate Mate as of August 2026. Those sectors rely on distributed product teams that build and iterate on AI features without requiring engineers to be on-site.
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