AI Automation Developer Jobs
AI Automation Developer jobs are open from new-grad to principal across technology, finance, healthcare, and manufacturing, with specializations in RPA, agentic AI workflows, and intelligent process automation. See the openings below and apply to the ones that match your experience.
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Karman Space & Defense is a leader in the rapid design, development, and production of critical, next-generation system solutions that align with the U.S. Department of War and its allies' core mission priorities, and meet the accelerating demand for access to space. Building on nearly 50 years of success, we deliver Payload & Protection Systems, Aero/Hydrodynamic Interstage Systems, and Propulsion & Launch Systems to more than 80 prime contractors supporting over 130 space and defense programs.
In this senior individual‑contributor role, you will translate Karman's enterprise artificial intelligence (AI) strategy into secure, scalable, and reusable architectures that accelerate responsible adoption across the organization. You will shape technical patterns, build reference implementations, evaluate emerging technologies, and establish guardrails that enable governed self‑service. Partnering closely with AI/Data & Automation, Business Systems, Cybersecurity, Infrastructure, and functional teams, you will provide hands‑on technical leadership that strengthens solution quality, operational consistency, and enterprise readiness.
Responsibilities
- Defines and evolves Karman's enterprise AI reference architecture.
- Establishes architectural patterns for model access, retrieval‑augmented generation (RAG), orchestration, agents, application programming interfaces (APIs), evaluation, observability, and cost management.
- Develops technical standards for Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, and other approved enterprise AI capabilities.
- Evaluates external platforms and models based on security, performance, cost, and business needs.
- Designs architectures that support portability using APIs, abstraction layers, open protocols, and exit strategies.
- Builds proofs of concept, reference implementations, reusable components, and technical accelerators.
- Provides hands‑on support for complex AI use cases, including RAG solutions, agentic workflows, model‑integrated applications, and automation.
- Establishes reusable templates, patterns, guardrails, and documentation to enable governed self‑service.
- Translates enterprise AI governance requirements into technical controls for identity, access, logging, monitoring, classification, retention, and human oversight.
- Defines evaluation, observability, quality, operational readiness, incident response, and lifecycle management standards for AI solutions.
Required Qualifications
- Significant experience in enterprise architecture, cloud architecture, software engineering, or platform engineering.
- Recent experience designing and deploying production generative artificial intelligence (AI) solutions.
- Strong working knowledge of the Microsoft cloud and AI ecosystem, including Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, Entra ID, Purview, and Microsoft security technologies.
- Hands‑on experience integrating commercial AI models through APIs and building model‑enabled applications.
- Strong understanding of RAG architectures, agent patterns, tool use, model orchestration, vector search, and enterprise data integration.
- Familiarity with standards and technologies such as Model Context Protocol (MCP), OpenTelemetry, open‑weight models, and modern inference platforms.
- Experience designing secure systems in regulated or high‑assurance environments.
- Ability and willingness to write code, build prototypes, review designs, and troubleshoot technical issues.
- Strong written and verbal communication skills with the ability to explain complex technical tradeoffs to technical and executive audiences.
Preferred Qualifications
- Experience in aerospace, defense, government, manufacturing, financial services, or other regulated industries.
- Experience with GCC High, sovereign cloud, restricted environments, or controlled‑data architectures.
- Familiarity with frameworks such as Cybersecurity Maturity Model Certification (CMMC), National Institute of Standards and Technology (NIST) Special Publication 800‑171, Controlled Unclassified Information (CUI), International Traffic in Arms Regulations (ITAR), NIST AI Risk Management Framework (RMF), and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 42001.
- Experience integrating AI with enterprise platforms such as enterprise resource planning (ERP), product lifecycle management (PLM), manufacturing execution systems (MES), customer relationship management (CRM), productivity, analytics, and workflow systems.
- Familiarity with graphics processing unit (GPU) infrastructure, self‑hosted models, fine‑tuning, and private inference environments.
- Relevant Microsoft, cloud, architecture, or security certifications.
This position requires U.S. person status under U.S. export control laws, including U.S. citizens and nationals, lawful permanent residents, refugees, and asylees.
Benefits
- Medical, dental, and vision insurance
- 401(k) with company match
- Paid time off
- Health Savings Account (HSA) with company contribution
- Flexible Spending Accounts (FSA)
- Company‑paid life and ADdummyamp;D insurance
- Short‑ and long‑term disability coverage
- Tuition reimbursement
Karman Space and Defense is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, or any other status protected by applicable federal, state, or local law.
View our Privacy Policy
Karman Space & Defense is a leader in the rapid design, development, and production of critical, next-generation system solutions that align with the U.S. Department of War and its allies' core mission priorities, and meet the accelerating demand for access to space. Building on nearly 50 years of success, we deliver Payload & Protection Systems, Aero/Hydrodynamic Interstage Systems, and Propulsion & Launch Systems to more than 80 prime contractors supporting over 130 space and defense programs.
In this senior individual‑contributor role, you will translate Karman's enterprise artificial intelligence (AI) strategy into secure, scalable, and reusable architectures that accelerate responsible adoption across the organization. You will shape technical patterns, build reference implementations, evaluate emerging technologies, and establish guardrails that enable governed self‑service. Partnering closely with AI/Data & Automation, Business Systems, Cybersecurity, Infrastructure, and functional teams, you will provide hands‑on technical leadership that strengthens solution quality, operational consistency, and enterprise readiness.
Responsibilities
- Defines and evolves Karman's enterprise AI reference architecture.
- Establishes architectural patterns for model access, retrieval‑augmented generation (RAG), orchestration, agents, application programming interfaces (APIs), evaluation, observability, and cost management.
- Develops technical standards for Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, and other approved enterprise AI capabilities.
- Evaluates external platforms and models based on security, performance, cost, and business needs.
- Designs architectures that support portability using APIs, abstraction layers, open protocols, and exit strategies.
- Builds proofs of concept, reference implementations, reusable components, and technical accelerators.
- Provides hands‑on support for complex AI use cases, including RAG solutions, agentic workflows, model‑integrated applications, and automation.
- Establishes reusable templates, patterns, guardrails, and documentation to enable governed self‑service.
- Translates enterprise AI governance requirements into technical controls for identity, access, logging, monitoring, classification, retention, and human oversight.
- Defines evaluation, observability, quality, operational readiness, incident response, and lifecycle management standards for AI solutions.
Required Qualifications
- Significant experience in enterprise architecture, cloud architecture, software engineering, or platform engineering.
- Recent experience designing and deploying production generative artificial intelligence (AI) solutions.
- Strong working knowledge of the Microsoft cloud and AI ecosystem, including Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Fabric, Entra ID, Purview, and Microsoft security technologies.
- Hands‑on experience integrating commercial AI models through APIs and building model‑enabled applications.
- Strong understanding of RAG architectures, agent patterns, tool use, model orchestration, vector search, and enterprise data integration.
- Familiarity with standards and technologies such as Model Context Protocol (MCP), OpenTelemetry, open‑weight models, and modern inference platforms.
- Experience designing secure systems in regulated or high‑assurance environments.
- Ability and willingness to write code, build prototypes, review designs, and troubleshoot technical issues.
- Strong written and verbal communication skills with the ability to explain complex technical tradeoffs to technical and executive audiences.
Preferred Qualifications
- Experience in aerospace, defense, government, manufacturing, financial services, or other regulated industries.
- Experience with GCC High, sovereign cloud, restricted environments, or controlled‑data architectures.
- Familiarity with frameworks such as Cybersecurity Maturity Model Certification (CMMC), National Institute of Standards and Technology (NIST) Special Publication 800‑171, Controlled Unclassified Information (CUI), International Traffic in Arms Regulations (ITAR), NIST AI Risk Management Framework (RMF), and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 42001.
- Experience integrating AI with enterprise platforms such as enterprise resource planning (ERP), product lifecycle management (PLM), manufacturing execution systems (MES), customer relationship management (CRM), productivity, analytics, and workflow systems.
- Familiarity with graphics processing unit (GPU) infrastructure, self‑hosted models, fine‑tuning, and private inference environments.
- Relevant Microsoft, cloud, architecture, or security certifications.
This position requires U.S. person status under U.S. export control laws, including U.S. citizens and nationals, lawful permanent residents, refugees, and asylees.
Benefits
- Medical, dental, and vision insurance
- 401(k) with company match
- Paid time off
- Health Savings Account (HSA) with company contribution
- Flexible Spending Accounts (FSA)
- Company‑paid life and ADdummyamp;D insurance
- Short‑ and long‑term disability coverage
- Tuition reimbursement
Karman Space and Defense is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, or any other status protected by applicable federal, state, or local law.
View our Privacy Policy
AI Automation Developer Jobs by Experience Level
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Find AI Automation Developer JobsAI Automation Developer Job Market
Who's Hiring
- Booz Allen Hamilton20
- JPMorganChase11
- Johns Hopkins University Applied Physics Laboratory9
- University of San Diego6
- Penn State University4
Top Industries Hiring
- Education
- Technology & Software
- Banking & Financial Services
- Healthcare & Medical Services
- Insurance
What Employers Look For
The qualifications that appear most often in AI automation developer jobs.
- Proficiency in at least one RPA platform such as UiPath, Automation Anywhere, or Power Automate
- Experience building and deploying Python or JavaScript-based automation scripts in production environments
- Familiarity with LLMs and prompt engineering for integrating AI into automated workflows
- Knowledge of REST APIs and integration patterns for connecting enterprise systems and third-party services
- Experience with workflow orchestration tools such as Apache Airflow, Prefect, or cloud-native equivalents
- Bachelor's degree in computer science, software engineering, or a related technical discipline
Tips for Your AI Automation Developer Job Search
Tailor your resume to automation stacks
Generic developer resumes miss the mark here. Call out the specific tools you've used, whether that's UiPath, Power Automate, Python-based orchestration, or LLM-integrated pipelines. Recruiters scanning for automation roles need to see the stack, not just 'automation experience.'
Show before-and-after impact in projects
Hiring managers want proof your automations moved a real needle. Describe the manual process, what you built, and the measurable outcome, like hours saved per week or error rate reduction. Vague claims about 'improving efficiency' don't stand out in a crowded applicant pool.
Apply early to roles that fit
Migrate Mate lists ai automation developer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter for roles that match your automation layer
AI automation developer postings vary widely: some focus on RPA bots, others on ML pipeline orchestration or agentic frameworks like LangGraph. Targeting your search by the technology layer you know best, rather than the job title alone, surfaces roles where you're a genuine fit.
Prepare a live demo for technical screens
Many interviews for this role include a live build exercise. Prepare a short, deployable automation you can walk through end-to-end, ideally one that shows error handling, logging, and a real-world trigger. Candidates who demo working code move further than those who describe past work alone.
Negotiate scope alongside compensation
AI automation roles often evolve quickly, and the initial job description may understate what you'll own. During the offer stage, ask directly which workflows are already built, which are greenfield, and what the roadmap looks like for agentic capabilities so you can evaluate growth alongside pay.
AI Automation Developer Jobs: Frequently Asked Questions
Which companies are hiring the most ai automation developers?
Booz Allen Hamilton, JPMorganChase, and Johns Hopkins University Applied Physics Laboratory are hiring the most ai automation developers right now, with openings concentrated in Virginia, California, and Texas, based on current listings on Migrate Mate as of November 2026. Demand is especially strong in companies undergoing large-scale digital transformation or deploying agentic AI products.
How many ai automation developer jobs are remote?
About 57% of ai automation developer openings are fully remote or hybrid as of November 2026, reflecting strong employer flexibility for this role. Sub-areas like RPA development, Python scripting, and LLM workflow integration tend to have the highest remote availability, while on-site requirements are more common for roles tied to manufacturing or regulated industries.
How do you become an ai automation developer?
Start by building a foundation in a scripting language like Python and learning at least one RPA platform through its free certification track. Next, work through hands-on projects that connect real systems using APIs and webhooks. Add LLM integration skills by building a simple agentic workflow. Publish your projects publicly so employers can review working code rather than a resume description alone.
Can you get hired as an ai automation developer with little experience?
Yes, especially if you can demonstrate working automations rather than just coursework. Build a small portfolio of three to five real projects that each solve a distinct problem, such as an RPA bot handling a data entry task, a Python script triggering on an API event, and a simple LLM-powered workflow. Entry-level roles in internal IT automation or operations teams are the most accessible starting points.
What does the ai automation developer interview process look like?
Most processes start with a recruiter screen focused on your tool experience and past projects, followed by a technical phone or video round where you walk through a previous automation end-to-end. A live coding or build exercise typically comes next, often asking you to wire together an API call, a conditional logic layer, and an output handler. Final rounds usually involve a system design discussion with engineering or architecture leads.
Where can I find and apply to ai automation developer jobs?
You can find and apply to ai automation developer jobs on Migrate Mate, which lists current openings from across the United States in one place. Search for roles that match your stack and experience level, then apply directly to each listing that fits.
See All 313+ AI Automation Developer Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI Automation Developer Jobs