Remote AI Data Engineer Jobs
Remote AI Data Engineer jobs are in active demand across the U.S., with remote-first firms and distributed teams hiring across technology, financial services, and healthcare. Employers hiring remotely right now include CVS Health, Alvarez & Marsal, and Netflix. See the openings below and apply to the ones that match your experience.
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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
See All 506+ Remote AI Data Engineer Jobs
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Find Remote AI Data Engineer JobsRemote AI Data Engineer Job Market
Who's Hiring
- CVS Health34
- Alvarez & Marsal26
- Netflix19
- Liberty Mutual Insurance14
- Airbnb12
Top Industries Hiring
- Technology & Software146
- Consulting & Professional Services71
- Healthcare & Medical Services56
- Investment & Asset Management31
- Accounting & Auditing27
What Employers Look For
The qualifications that appear most often in remote AI data engineer jobs.
- Proficiency in Python and SQL for data pipeline development and transformation
- Experience building and maintaining ML feature pipelines or data platforms at scale
- Hands-on work with orchestration tools such as Apache Airflow, Prefect, or Dagster
- Familiarity with cloud data platforms including AWS, GCP, or Azure data services
- Knowledge of streaming frameworks such as Apache Kafka or Apache Flink
- Bachelor's degree in computer science, data engineering, or a related technical field
Tips for Your Remote AI Data Engineer Job Search
Show async collaboration in your portfolio
Remote employers want evidence you can work without constant check-ins. Document your projects with written READMEs, architecture decision records, and inline comments, because that's the kind of self-explaining output distributed teams depend on from a remote ai data engineer.
Apply early to remote roles that fit
Migrate Mate lists remote ai data engineer openings from across the U.S. in one place, so you can find roles that match your stack and apply directly without sorting through irrelevant on-site listings.
Highlight your remote AI toolchain explicitly
Call out the specific tools you use for distributed AI workflows, such as MLflow for experiment tracking, Airflow for orchestration, or dbt for transformation, because remote hiring managers scan for these to judge whether you'll ramp up without in-person training.
Prepare for async-style remote interviews
Many remote teams use take-home assessments or recorded video answers before any live call. Practice explaining your pipeline design decisions in writing and on camera, since remote ai data engineer interviews often weigh your communication clarity as much as your technical output.
Target remote-first companies in your outreach
Remote-first firms have already solved the infrastructure and culture problems that make remote data engineering work. Prioritize companies whose career pages, engineering blogs, or job descriptions explicitly describe distributed or async-first teams, because those roles are built for remote execution from day one.
Remote AI Data Engineer Jobs: Frequently Asked Questions
How do I get a remote ai data engineer job?
Target companies built on distributed teams, such as remote-first software firms and cloud-native startups, because they already have the infrastructure for async collaboration. Remote employers screen hard for self-direction, clear written communication, and hands-on proficiency with tools like dbt, Spark, Airflow, and vector databases. A public GitHub repo or portfolio project that shows an end-to-end AI pipeline gives you a concrete edge over candidates who only list skills.
Which companies hire remote ai data engineers?
Employers currently hiring remote ai data engineers include CVS Health, Alvarez & Marsal, and Netflix, per current remote listings on Migrate Mate as of June 2026. Remote-first technology firms, fintech scale-ups, and distributed healthcare data teams make up the bulk of hiring for this role.
Can you get a remote ai data engineer job with no experience?
Yes, but remote entry-level roles are harder to land because you're expected to work independently from day one without in-office support. Remote-first startups and smaller distributed teams are more open to junior candidates than large enterprises. Build a demonstrable project, such as a deployed ML pipeline or a public data transformation repo, to show you can execute without hand-holding, and that's often what opens the door.
Do you need a degree for remote ai data engineer jobs?
Not always. Remote employers place significant weight on demonstrated skills, real project output, and familiarity with the modern AI and data stack over formal credentials. A strong portfolio, proficiency in Python, SQL, and ML frameworks, and evidence of shipping production-grade pipelines can carry more weight than a degree, particularly at remote-first companies that evaluate candidates on async work samples.
Which industries hire the most remote ai data engineers?
Remote ai data engineer roles concentrate in Technology & Software, Consulting & Professional Services, and Healthcare & Medical Services, based on current remote listings on Migrate Mate as of June 2026. Those sectors rely on distributed data teams to build and maintain AI pipelines that don't require anyone to be physically on-site.
See All 506+ Remote AI Data Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote AI Data Engineer Jobs