Remote AI Platform Engineer Jobs
Remote AI Platform Engineer jobs are in active demand across the U.S., with remote-first firms and distributed engineering teams hiring for roles in cloud infrastructure, MLOps, and enterprise AI across software, finance, and healthcare. Employers hiring remotely right now include CVS Health, Netflix, and Airbnb. Scan the live roles below and apply to whichever ones fit.
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Title: AI Engineer
Duration: 6 Months
Location: Remote
Job Description:
Role Summary
We have a capable engineering team working on a complex legacy-to-Python migration and multiple customer-facing platforms. We don't need another developer — we need someone whose primary job is to make the entire team 3-5x faster by building AI-powered automation across every phase of the SDLC: requirements extraction, code generation, testing, defect analysis, and release. This person doesn't just use AI — they architect AI-driven engineering workflows that multiply the output of every developer on the team.
Required Skills (Must-Have):
- AI Agent Development & Orchestration: #1 differentiator. Proven experience building multi-step AI agent workflows for engineering tasks — chaining code analysis, generation, validation, feedback. GitHub Copilot, Claude, LangChain, custom agents, or equivalent.
- SDLC Automation & DevOps: Track record of automating significant portions of the delivery lifecycle — CI/CD, automated testing, code quality gates, release automation (GitHub Actions).
- Python (strong proficiency): Primary codebase is Python — data processing, JSON transformations, modular architecture. Must build tooling and review/generate code at scale.
- Automated Testing Frameworks: AI-augmented regression suites, diff/comparison tooling, scenario-based test generation, golden-file validation. pytest, CI integration.
- Advanced Prompt Engineering: Complex multi-step prompts for code generation, legacy code analysis, business rule extraction. Knows how to structure context, manage token limits, and validate AI outputs.
Requirements
- 7+ years of experience
Preferred Skills
- Legacy code analysis — Parsing unfamiliar proprietary languages to extract business logic via AI
- Java / Spring Boot — Secondary platforms are Java-based
- Elasticsearch, Azure / AKS / Cosmos DB — Platform technologies
- Healthcare data / MDM domain
Key Attributes
- AI-native thinker — Every manual process is an automation opportunity. AI is the primary development engine, not a side tool.
- Force multiplier — Measures success by how much faster they make the entire team, not by their own code output
- Builder of systems — Creates reusable tooling, agent templates, and playbooks the whole team adopts
- Pragmatic and fast — Ships working automation in days, not weeks. Iterates rapidly.
Environment
Python, Java/Spring Boot, Elasticsearch, Azure (AKS, Cosmos DB), GitHub, Jira, HPCC/ECL (legacy) | GitHub Copilot, Claude, SDD, AI-DLC | Agile, 2-week sprints
Title: AI Engineer
Duration: 6 Months
Location: Remote
Job Description:
Role Summary
We have a capable engineering team working on a complex legacy-to-Python migration and multiple customer-facing platforms. We don't need another developer — we need someone whose primary job is to make the entire team 3-5x faster by building AI-powered automation across every phase of the SDLC: requirements extraction, code generation, testing, defect analysis, and release. This person doesn't just use AI — they architect AI-driven engineering workflows that multiply the output of every developer on the team.
Required Skills (Must-Have):
- AI Agent Development & Orchestration: #1 differentiator. Proven experience building multi-step AI agent workflows for engineering tasks — chaining code analysis, generation, validation, feedback. GitHub Copilot, Claude, LangChain, custom agents, or equivalent.
- SDLC Automation & DevOps: Track record of automating significant portions of the delivery lifecycle — CI/CD, automated testing, code quality gates, release automation (GitHub Actions).
- Python (strong proficiency): Primary codebase is Python — data processing, JSON transformations, modular architecture. Must build tooling and review/generate code at scale.
- Automated Testing Frameworks: AI-augmented regression suites, diff/comparison tooling, scenario-based test generation, golden-file validation. pytest, CI integration.
- Advanced Prompt Engineering: Complex multi-step prompts for code generation, legacy code analysis, business rule extraction. Knows how to structure context, manage token limits, and validate AI outputs.
Requirements
- 7+ years of experience
Preferred Skills
- Legacy code analysis — Parsing unfamiliar proprietary languages to extract business logic via AI
- Java / Spring Boot — Secondary platforms are Java-based
- Elasticsearch, Azure / AKS / Cosmos DB — Platform technologies
- Healthcare data / MDM domain
Key Attributes
- AI-native thinker — Every manual process is an automation opportunity. AI is the primary development engine, not a side tool.
- Force multiplier — Measures success by how much faster they make the entire team, not by their own code output
- Builder of systems — Creates reusable tooling, agent templates, and playbooks the whole team adopts
- Pragmatic and fast — Ships working automation in days, not weeks. Iterates rapidly.
Environment
Python, Java/Spring Boot, Elasticsearch, Azure (AKS, Cosmos DB), GitHub, Jira, HPCC/ECL (legacy) | GitHub Copilot, Claude, SDD, AI-DLC | Agile, 2-week sprints
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Find JobsRemote AI Platform Engineer Job Market
Who's Hiring
- CVS Health55
- Netflix10
- Airbnb8
- Block7
- Zillow7
Top Industries Hiring
- Technology & Software93
- Healthcare & Medical Services59
- Consulting & Professional Services27
- Media & Entertainment13
- Hospitality & Tourism11
What Employers Look For
The qualifications that appear most often in remote AI platform engineer jobs.
- Proficiency in Python and at least one infrastructure-as-code tool such as Terraform
- Hands-on experience with Kubernetes, Docker, and container orchestration at scale
- Experience building or maintaining MLOps pipelines using tools like Kubeflow, MLflow, or similar
- Familiarity with major cloud platforms including AWS, Google Cloud, or Microsoft Azure
- Bachelor's degree in computer science, engineering, or a related technical field
- Experience with data pipeline frameworks such as Apache Spark, Airflow, or Ray
Tips for Your Remote AI Platform Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote ai platform engineer openings from across the U.S. in one place. Search for roles that match your stack and experience level and apply directly, since remote postings at well-known companies fill quickly.
Document your async collaboration experience
Remote employers hire ai platform engineers who can move projects forward without constant check-ins. Your resume and cover letter should name specific async tools you've used, like Notion, Linear, or Slack threads, and show decisions you made and shipped independently.
Build a public AI infrastructure portfolio
Put your MLOps pipelines, model serving setups, or LLM orchestration work somewhere reviewable, whether a GitHub repository, a technical blog, or a demo environment. Remote hiring managers evaluate your work before they ever schedule a call.
Prepare for remote-first technical interviews
Expect live coding sessions in shared environments and system design discussions over video. Practice explaining your architecture decisions out loud and in writing, since remote teams assess both your technical depth and your ability to communicate complex infrastructure choices clearly.
Signal your remote readiness in every application
Call out distributed team experience, time zone flexibility, and written communication habits directly in your materials. Remote ai platform engineer roles attract strong candidates, so making your remote competence explicit, rather than assumed, moves your application forward faster.
Remote AI Platform Engineer Jobs: Frequently Asked Questions
How do I get a remote ai platform engineer job?
Target remote-first companies and distributed engineering teams, since they have established workflows for async collaboration and are more likely to onboard remote engineers successfully. Remote employers screen heavily for self-direction, clear written communication, and hands-on experience with MLOps tooling, cloud platforms, and LLM orchestration frameworks. Candidates who show previous async project delivery or open-source contributions in AI infrastructure stand out.
Which companies hire remote ai platform engineers?
Companies hiring remote ai platform engineers right now include CVS Health, Netflix, and Airbnb, based on current remote listings on Migrate Mate as of June 2026. Remote openings for this role concentrate at remote-first software companies, AI-native startups, and distributed teams in fintech and cloud services, where engineering teams operate across time zones and rely on async workflows.
Can you get a remote ai platform engineer job with no experience?
Yes, but remote entry-level roles are harder to land because employers expect you to work independently from day one without in-person onboarding support. The strongest path is building a public portfolio of AI infrastructure projects, contributing to open-source MLOps or LLM tooling repositories, and demonstrating written communication skills through documentation or technical writeups that show you can collaborate async.
Do you need a degree for remote ai platform engineer jobs?
Not always. Remote employers weigh demonstrated skills, shipped projects, and hands-on experience with cloud platforms, model serving infrastructure, and MLOps pipelines more heavily than a specific credential. A portfolio showing real AI infrastructure work, certifications from major cloud providers, and contributions to relevant open-source projects can carry as much weight as a formal degree for many remote teams.
Which industries hire the most remote ai platform engineers?
Most remote ai platform engineer openings sit in Technology & Software, Healthcare & Medical Services, and Consulting & Professional Services, per current remote listings on Migrate Mate as of June 2026. These sectors rely on distributed engineering teams that build and maintain AI infrastructure across multiple regions, making remote work a natural fit for the role.
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