Remote Agent Engineer Jobs
Remote agent engineer jobs are open across the U.S. at remote-first firms and distributed teams building AI-driven products, with strong demand in software, enterprise technology, and financial services. Employers hiring remote agent engineers right now include ServiceNow, Honeycomb.io, and QUO. See the openings below and apply to the ones that match your experience.
Find Remote Agent Engineer JobsOverview
Showing 5 of 23+ Remote Agent Engineer jobs
Job ID:
J54932
Job Title:
Senior AI Agent Engineer
Location:
Charlotte, NC
Duration:
24 Months + Extension
Domain Exposure:
Consumer Staples
Client:
To Be Discussed Later
Employment Type:
W-2, 1099, C2C
Work Authorization:
US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other
Job Title: Senior AI Agent Engineer
Location: Charlotte, NC(Remote)
Duration: 24 Months + Extension
Bill Rate: $69/hour (C2C)
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other
Job Description:
Design, develop, and harden production-grade AI agents across the end-to-end detect store plan remediate deploy lifecycle.
Build and orchestrate Finder, Planner, and Executor agents to identify issues, prioritize remediation, execute approved actions, validate changes, and support controlled deployments.
Develop agent orchestration and tool integrations using Model Context Protocol (MCP), tool calling, agent frameworks, and workflow engines such as Temporal.
Develop and integrate agents with the Actionable Observation store, Overwatch state machine and prioritization capabilities, and operator console.
Integrate agents with GitLab pipelines, GitLab CI/CD, JFrog Artifactory, canary deployment workflows, and Tenable Vulnerability Management (UVM) as a vulnerability-finding source.
Expose and consume enterprise knowledge graphs containing data lineage and environment context through MCP, ensuring agents have governed, read-only access to relevant information.
Implement event processing, data storage, and state management using Kafka, MongoDB, SQL, and SQLite.
Develop and query knowledge graphs using Neo4j and Cypher to support contextual retrieval, dependency analysis, and remediation planning.
Implement automated code-change workflows, AI-assisted code generation, test generation, and lockdown-test practices to validate remediation changes before deployment.
Apply context engineering and specification-driven development to improve agent accuracy, consistency, traceability, and maintainability.
Embed human-approval gates, audit trails, access controls, and AI governance controls throughout agent design, execution, and deployment.
Ensure autonomous workflows comply with enterprise security standards, change-management processes, deployment controls, and production-readiness requirements.
Support vulnerability remediation and software version-currency initiatives using CVE, EPSS, CVSS, End-of-Life (EOL), and End-of-Support (EOS) considerations.
Implement controlled deployment patterns, including canary releases and incremental rollouts, to reduce operational risk.
Troubleshoot agent execution failures, integration issues, workflow exceptions, and deployment problems; perform root-cause analysis and implement corrective actions.
Monitor and improve agent reliability, performance, scalability, and observability using Dynatrace or comparable tools where applicable.
Collaborate with application development, infrastructure, cybersecurity, DevSecOps, architecture, and production support teams to integrate agents into existing workflows.
Document reusable agent patterns, technical designs, integration approaches, governance controls, onboarding procedures, and operational best practices.
Coach application, infrastructure, and security teams on agent onboarding, secure usage, human oversight, and adoption of the autonomous operating model.
Participate in technical design reviews, code reviews, automated testing, release planning, and continuous improvement initiatives.
Own AI agent solutions across requirements, design, development, integration, testing, deployment, monitoring, and ongoing enhancement.
Basic Qualifications:
Minimum 7+ years of experience in software engineering or production application development, delivering and supporting enterprise-grade solutions.
Minimum 1–2+ years of hands-on experience developing LLM-based applications, Generative AI solutions, AI agents, or agentic workflows.
Minimum 3+ years of hands-on experience developing production software using Python and/or Java.
Minimum 3+ years of experience with Git, GitLab CI/CD, automated testing, and software delivery practices.
Minimum 1+ year of hands-on experience with AI agent orchestration, MCP, tool calling, and agent frameworks or equivalent technologies.
Minimum 1+ year of experience with agent development platforms such as AWS Agent Core, Kiro, or equivalent technologies.
Minimum 1+ year of experience with workflow orchestration engines such as Temporal or equivalent platforms.
Minimum 2+ years of experience developing automated code-change workflows, code validation, automated test generation, or lockdown-test practices.
Minimum 1+ year of practical experience applying context engineering and specification-driven development to AI or software engineering workflows.
Minimum 2+ years of experience working with event-processing or data-storage technologies such as Kafka, MongoDB, SQL, or SQLite.
Minimum 1+ year of experience with Neo4j, Cypher, graph databases, or knowledge-graph querying.
Minimum 3+ years of experience integrating applications with CI/CD pipelines, artifact repositories, deployment platforms, or enterprise tools.
Minimum 2+ years of experience implementing secure software engineering practices, access controls, audit trails, or human-in-the-loop approval mechanisms.
Minimum 1+ year of experience implementing AI governance, security guardrails, or operational controls for AI-driven automation.
Minimum 3+ years of experience with SDLC, automated testing, change management, release processes, and production support.
Minimum 3+ years of experience troubleshooting complex application or integration issues, conducting root-cause analysis, and implementing corrective actions.
Minimum 2+ years of experience collaborating with cross-functional teams, including application development, infrastructure, DevOps, or cybersecurity.
Minimum 1+ year of experience documenting technical designs, reusable engineering patterns, operational procedures, or implementation standards.
Minimum 1+ year of experience providing technical guidance, mentoring engineers, or coaching teams on engineering practices or new technology adoption.
Demonstrated ability to explain personal technical contributions, agent architecture, implementation decisions, challenges, and business outcomes from previous projects
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
Job ID:
J54932
Job Title:
Senior AI Agent Engineer
Location:
Charlotte, NC
Duration:
24 Months + Extension
Domain Exposure:
Consumer Staples
Client:
To Be Discussed Later
Employment Type:
W-2, 1099, C2C
Work Authorization:
US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other
Job Title: Senior AI Agent Engineer
Location: Charlotte, NC(Remote)
Duration: 24 Months + Extension
Bill Rate: $69/hour (C2C)
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other
Job Description:
Design, develop, and harden production-grade AI agents across the end-to-end detect store plan remediate deploy lifecycle.
Build and orchestrate Finder, Planner, and Executor agents to identify issues, prioritize remediation, execute approved actions, validate changes, and support controlled deployments.
Develop agent orchestration and tool integrations using Model Context Protocol (MCP), tool calling, agent frameworks, and workflow engines such as Temporal.
Develop and integrate agents with the Actionable Observation store, Overwatch state machine and prioritization capabilities, and operator console.
Integrate agents with GitLab pipelines, GitLab CI/CD, JFrog Artifactory, canary deployment workflows, and Tenable Vulnerability Management (UVM) as a vulnerability-finding source.
Expose and consume enterprise knowledge graphs containing data lineage and environment context through MCP, ensuring agents have governed, read-only access to relevant information.
Implement event processing, data storage, and state management using Kafka, MongoDB, SQL, and SQLite.
Develop and query knowledge graphs using Neo4j and Cypher to support contextual retrieval, dependency analysis, and remediation planning.
Implement automated code-change workflows, AI-assisted code generation, test generation, and lockdown-test practices to validate remediation changes before deployment.
Apply context engineering and specification-driven development to improve agent accuracy, consistency, traceability, and maintainability.
Embed human-approval gates, audit trails, access controls, and AI governance controls throughout agent design, execution, and deployment.
Ensure autonomous workflows comply with enterprise security standards, change-management processes, deployment controls, and production-readiness requirements.
Support vulnerability remediation and software version-currency initiatives using CVE, EPSS, CVSS, End-of-Life (EOL), and End-of-Support (EOS) considerations.
Implement controlled deployment patterns, including canary releases and incremental rollouts, to reduce operational risk.
Troubleshoot agent execution failures, integration issues, workflow exceptions, and deployment problems; perform root-cause analysis and implement corrective actions.
Monitor and improve agent reliability, performance, scalability, and observability using Dynatrace or comparable tools where applicable.
Collaborate with application development, infrastructure, cybersecurity, DevSecOps, architecture, and production support teams to integrate agents into existing workflows.
Document reusable agent patterns, technical designs, integration approaches, governance controls, onboarding procedures, and operational best practices.
Coach application, infrastructure, and security teams on agent onboarding, secure usage, human oversight, and adoption of the autonomous operating model.
Participate in technical design reviews, code reviews, automated testing, release planning, and continuous improvement initiatives.
Own AI agent solutions across requirements, design, development, integration, testing, deployment, monitoring, and ongoing enhancement.
Basic Qualifications:
Minimum 7+ years of experience in software engineering or production application development, delivering and supporting enterprise-grade solutions.
Minimum 1–2+ years of hands-on experience developing LLM-based applications, Generative AI solutions, AI agents, or agentic workflows.
Minimum 3+ years of hands-on experience developing production software using Python and/or Java.
Minimum 3+ years of experience with Git, GitLab CI/CD, automated testing, and software delivery practices.
Minimum 1+ year of hands-on experience with AI agent orchestration, MCP, tool calling, and agent frameworks or equivalent technologies.
Minimum 1+ year of experience with agent development platforms such as AWS Agent Core, Kiro, or equivalent technologies.
Minimum 1+ year of experience with workflow orchestration engines such as Temporal or equivalent platforms.
Minimum 2+ years of experience developing automated code-change workflows, code validation, automated test generation, or lockdown-test practices.
Minimum 1+ year of practical experience applying context engineering and specification-driven development to AI or software engineering workflows.
Minimum 2+ years of experience working with event-processing or data-storage technologies such as Kafka, MongoDB, SQL, or SQLite.
Minimum 1+ year of experience with Neo4j, Cypher, graph databases, or knowledge-graph querying.
Minimum 3+ years of experience integrating applications with CI/CD pipelines, artifact repositories, deployment platforms, or enterprise tools.
Minimum 2+ years of experience implementing secure software engineering practices, access controls, audit trails, or human-in-the-loop approval mechanisms.
Minimum 1+ year of experience implementing AI governance, security guardrails, or operational controls for AI-driven automation.
Minimum 3+ years of experience with SDLC, automated testing, change management, release processes, and production support.
Minimum 3+ years of experience troubleshooting complex application or integration issues, conducting root-cause analysis, and implementing corrective actions.
Minimum 2+ years of experience collaborating with cross-functional teams, including application development, infrastructure, DevOps, or cybersecurity.
Minimum 1+ year of experience documenting technical designs, reusable engineering patterns, operational procedures, or implementation standards.
Minimum 1+ year of experience providing technical guidance, mentoring engineers, or coaching teams on engineering practices or new technology adoption.
Demonstrated ability to explain personal technical contributions, agent architecture, implementation decisions, challenges, and business outcomes from previous projects
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
See All 23 Remote Agent Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Agent Engineer JobsRemote Agent Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Media & Entertainment
What Employers Look For
The qualifications that appear most often in remote agent engineer jobs.
- Proficiency in Python and at least one agent framework such as LangChain or AutoGen
- Experience building or deploying systems that use large language model APIs
- Familiarity with tool-use patterns, function calling, and retrieval-augmented generation
- Ability to design and run evaluation pipelines for agent reliability and accuracy
- Experience with cloud platforms such as AWS, Azure, or Google Cloud for inference and orchestration
- Bachelor's degree in computer science, engineering, or a related technical field
Tips for Your Remote Agent Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote agent engineer openings from companies across the U.S. in one place, so you can find roles that match your stack and apply directly without digging through unfiltered results.
Show your agent systems in a public repo
Remote hiring managers for agent engineer roles want proof you can ship independently. Host documented projects on a public repository, covering your architecture decisions, tool-use patterns, and how you handled failures in multi-step agent pipelines.
Lead with async communication in applications
Distributed teams screen for written clarity before anything else. Write your cover message and application responses the way you would a detailed async Slack thread: direct, structured, and self-contained, with no assumption of a follow-up call to clarify.
Prepare for remote-first technical interviews
Remote agent engineer interviews often include take-home system design tasks or live coding sessions over shared editors. Practice walking through agentic workflow design out loud over video, since remote teams assess communication quality alongside technical judgment.
Remote Agent Engineer Jobs: Frequently Asked Questions
How do I get a remote agent engineer job?
Target remote-first companies and distributed product teams, since they have the infrastructure and culture to onboard agent engineers without an office. Remote employers screen hard for self-direction, clear async written communication, and hands-on experience with LLM orchestration, agentic frameworks, and tool-use patterns. A portfolio of deployed agent systems, open-source contributions, or documented side projects gives you a concrete edge over candidates with similar resumes but no visible remote output.
Which companies hire remote agent engineers?
Employers currently hiring remote agent engineers include ServiceNow, Honeycomb.io, and QUO, per current remote listings on Migrate Mate as of November 2026. Remote-first software companies, distributed AI product teams, and enterprise technology firms account for the largest share of these openings.
Can you get a remote agent engineer job with no experience?
Yes, but remote entry-level agent engineer roles are harder to land because employers expect you to work independently from day one with minimal hand-holding. Focus on companies building early-stage AI products, where small distributed teams value initiative over credentials. Build and document personal agent projects using public LLM APIs, contribute to open-source agentic frameworks, and demonstrate clear written communication, since that last point is non-negotiable for remote work.
Do you need a degree for remote agent engineer jobs?
Not always. Remote employers in this field tend to prioritize demonstrated skill over formal credentials, especially at companies moving fast on AI products. What carries real weight is a portfolio of working agent systems, fluency with orchestration frameworks, and evidence you can communicate clearly in writing across time zones. A degree in computer science or a related field helps, but many hiring teams will hire without one if your work speaks for itself.
Which industries hire the most remote agent engineers?
The sectors hiring the most remote agent engineers are Technology & Software and Media & Entertainment, based on current remote listings on Migrate Mate as of November 2026. These industries rely on distributed engineering teams and are actively integrating autonomous agent systems into their core products and workflows.
See All 23 Remote Agent Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Agent Engineer Jobs