Remote Software Engineer AI Jobs
Remote software engineer AI jobs are open across the U.S. in sectors like enterprise software, cloud infrastructure, fintech, and healthcare technology, at companies ranging from AI-native startups to large distributed engineering teams. Employers hiring remotely right now include Asana, Block, and Cribl. See the openings below and apply to the ones that match your experience.
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Granicus is driven by the excitement of building, implementing, and maintaining technology that is transforming the Govtech industry by bringing governments and its constituents together. We are on a mission to support our customers with meeting the needs of their communities and implementing our technology in ways that are equitable and inclusive. Granicus has consistently appeared on the GovTech 100 list over the past 5 years and has been recognized as the best companies to work on BuiltIn.
Over the last 25 years, we have served 5,500 federal, state, and local government agencies and more than 300 million citizen subscribers power an unmatched Subscriber Network that use our digital solutions to make the world a better place. With comprehensive cloud-based solutions for communications, government website design, meeting and agenda management software, records management, and digital services, Granicus empowers stronger relationships between government and residents across the U.S., U.K., Australia, New Zealand, and Canada. By simplifying interactions with residents, while disseminating critical information, Granicus brings governments closer to the people they serve—driving meaningful change for communities around the globe.
Want to know more? See more of what we do here.
Granicus serves more than 7,000 public-sector agencies and powers approximately 30 billion digital interactions annually. Within the Office of the CTO, we operate an AI-native software development lifecycle: a production engineering model in which autonomous agents perform high-confidence implementation work and senior engineers orchestrate, review, and own the outcome. The model is established and operating; we are scaling it across additional delivery teams.
This role joins one of those teams. Our engineering standards are calibrated to the practices used by leading software and AI organizations — generator-verifier architecture, eval-driven development, staged deployment, and high-volume autonomous pull-request pipelines — operated within a FedRAMP-authorized environment. We are hiring practitioners who will set and uphold these standards, not engineers who simply use AI tooling.
Operating constraints (non-negotiable): agents execute only within branches; all agent-generated code passes senior human review before merging to production; autonomous execution is a force multiplier and does not transfer accountability away from the responsible engineer. Compliance obligations — NIST 800-53 Rev 5, WCAG, SOC 2, and applicable FedRAMP authorizations — are treated as engineering requirements and a source of competitive advantage.
Why this role exists
When agents produce the majority of initial implementation, the scarce engineering skill shifts from authoring code to directing it, reviewing it rigorously at volume, and owning whether it is correct. This role is for a senior engineer who has made that transition: decomposing work for the agent array, authoring the evaluation suites that hold agent output to a measurable standard, reviewing agent-generated pull requests with greater rigor than most engineers apply to their own work, and shipping production code within a FedRAMP-authorized environment. The role contributes to defining how engineers operate in an AI-native lifecycle, not merely to adopting AI tooling.
What Your Impact Will Look Like:- Direct the agent array on production workstreams — decompose problems into tasks suitable for agent execution, dispatch them, and integrate the output into shipped software.
- Review agent-generated pull requests at volume and at depth — identify correctness, security, and accessibility defects that automated tests do not catch, while maintaining review throughput and a consistent quality bar.
- Author evaluation suites that make quality measurable — define criteria under which the pipeline validates correctness rather than relying on subjective assessment. Eval-driven development is your standard practice.
- Own quality end to end — correctness, performance, security posture, and WCAG accessibility of the software your team ships, irrespective of which component or agent produced the initial implementation.
- Advance workstreams along the autonomy ladder on the basis of evidence — move work from supervised to autonomous execution when measured reliability supports it, and revert promptly when it does not.
- Strengthen the development lifecycle itself — identify where patterns, prompts, or pipeline components degrade at volume and work with the lead architect to remediate them.
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Maintain agent operations within the security boundary — branch-only execution, vaulted credentials, sandboxed actions, and in-VPC inference. Throughput does not justify exceptions.
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OWNERSHIP FROM DAY ONE
- An active workstream directed through the agent array
- Agent pull-request review as a core, high-signal responsibility
- Evaluation suites authored and owned for your team’s deliverables
- End-to-end quality ownership within the FedRAMP-authorized environment
SCOPE YOU WILL GROW INTO- Higher autonomy ratios substantiated by reliability data
- Reusable prompt and evaluation patterns adopted by other engineers
- Contribution to the lifecycle standards as a co-author, not only a user
- Mentorship of engineers transitioning to agent-directed delivery
Required
- Strong engineering fundamentals. Data structures, systems design, and testing, with the ability to read unfamiliar code quickly and assess it accurately. Agents amplify engineering judgment; they do not substitute for it.
- A record of shipping production software you owned the quality of, including responsibility for diagnosis and remediation when it failed.
- Hands-on experience directing coding agents on production work, including their failure modes and the practice of reviewing agent-generated code critically rather than approving it by default.
- Demonstrated code-review competence. You identify defects that automated tests do not catch, provide actionable feedback, and maintain a high bar without becoming a bottleneck.
- High autonomy. You advance work without step-by-step direction and escalate issues proactively.
Preferred
- High-assurance or regulated experience. Shipping within FedRAMP, defense, financial services, healthcare, or another NIST 800-53 / SOC 2 / HIPAA-bound environment.
- Depth in evaluation authoring or test-first development within a rigorous engineering culture.
- Full-stack range, sufficient to review front-end and back-end agent output with equal confidence.
- Public-sector or govtech experience and familiarity with the relevant end users.
Indicators of a strong fit
- You deliver more effectively by directing multiple agents than by authoring code directly, while retaining a precise understanding of the intended implementation.
- You regard rigorous code review as a core engineering competency.
- You prefer to establish quality through evaluation suites rather than through discussion.
- You treat the agent array as leverage and reliably identify when its output is incorrect.
- You want to contribute to how engineering is practiced here, not only to apply new tooling.
Indicators this role is not a fit
- You measure your contribution by lines of code personally authored. That metric does not apply in this model.
- You approve pull requests without thorough review under time pressure. At agent volume, this is the primary path by which defects reach production.
- You are uncomfortable owning quality for code you did not author. Ownership here is intentionally decoupled from authorship.
- You regard evaluation and compliance as impediments to shipping.
- You prefer narrowly scoped tickets and no involvement in how the system operates.
Security and Privacy Requirements
- Responsible for Granicus information security by appropriately preserving the Confidentiality, Integrity, and Availability (CIA) of Granicus information assets in accordance with the company's information security program.
- Responsible for ensuring the data privacy of our employees and customers, their data, as well as taking all required privacy training in a timely manner, in accordance with company policies.
The Team
- We are a remote-first company with a globally distributed workforce across the United States, Canada, United Kingdom, India, Armenia, Australia, and New Zealand.
The Culture
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At Granicus, we are building a transparent, inclusive, and safe space for everyone who wants to be
a part of our journey. - A few culture highlights include – Employee Resource Groups to encourage diverse voices
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Coffee with Mark sessions – Our employees get to interact with our CEO on very important and
sometimes difficult issues ranging from mental health to work-life balance and current affairs. - Microsoft Teams communities focused on wellness, art, furbabies, family, parenting, and more.
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We bring in special guests from time to time to discuss issues that impact our employee
population
The Impact
- We are proud to serve dynamic organizations around the globe that use our digital solutions to make the world a better place — quite literally. We have so many powerful success stories that illustrate how our solutions are impacting the world. See more of our impact here.
Here’s what you can expect as a U.S.-based team member:
Flexibility & Balance
- Flexible Time Off – Take the time you need to rest, recharge, and live your life.
- Company-Wide Wellbeing Days – Paid days off to unplug and focus on your mental health.
- Work From Home Reimbursement – Support a productive home office environment.
- Multiple Health Plan Options – Including a 100% employer-paid plan.
- Employer HSA Contributions – When enrolled in a High-Deductible Health Plan.
- Fitness Reimbursement Program – Stay active, your way.
- On-Demand Mental Health Support – Access to Headspace and other wellness tools.
- Paid Parental Leave – For both birthing and non-birthing parents.
- Traditional & Roth 401(k) – With a generous company match.
- Life & AD&D Insurance – 100% employer-paid coverage for peace of mind.
- Online Learning Platforms – Fuel your professional development.
- Competitive Salary & Bonuses – Your contributions are valued and rewarded.
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Who's Hiring



Top Industries Hiring
- Technology & Software13
- Consulting & Professional Services3
- Education2
- Insurance2
- Music1
What Employers Look For
The qualifications that appear most often in remote software engineer AI jobs.
- Bachelor's or master's degree in computer science, machine learning, or a related field
- Proficiency in Python and hands-on experience with PyTorch or TensorFlow
- Experience building, fine-tuning, or deploying large language models or foundation models
- Familiarity with cloud ML platforms such as AWS SageMaker, Google Vertex AI, or Azure ML
- Understanding of MLOps practices including model versioning, monitoring, and CI/CD for ML pipelines
- Experience with data pipelines, feature engineering, and working with large-scale datasets
Tips for Your Remote Software Engineer AI Job Search
Build a portfolio that proves remote readiness
Remote employers can't watch you work, so your code does the talking. Host completed AI projects on GitHub with clear READMEs, documented model choices, and deployment instructions. Shipped work that a stranger can run and evaluate is far more persuasive than a list of skills on a resume.
Signal async communication skills in every application
Remote software engineer AI teams run on written communication. Your cover letter, GitHub commit messages, and pull request descriptions are all live samples. Write clearly, explain decisions, and avoid jargon. Employers notice when a candidate can communicate complex model behavior in plain, structured prose.
Apply early to remote roles that fit
Migrate Mate lists remote software engineer AI openings from across the U.S. in one place, so you can find roles that match your stack and experience level and apply directly without sorting through unrelated listings.
Prepare for asynchronous technical screenings
Many remote AI teams use take-home assessments or recorded coding exercises instead of live interviews. Practice explaining your reasoning in writing as you work through problems. Reviewers evaluate not just your solution but how clearly you articulate your approach, trade-offs, and assumptions.
Remote Software Engineer AI Jobs: Frequently Asked Questions
How do I get a remote software engineer AI job?
Remote software engineer AI roles go to candidates who can demonstrate independent execution, not just technical skill. Remote employers screen for proficiency in ML frameworks like PyTorch or TensorFlow, experience deploying models to production, and strong async written communication. What gives you an edge is a portfolio of shipped AI work, contributions to open-source projects, and a history of collaborating across time zones without close supervision.
Which companies hire remote software engineer AIs?
Companies hiring remote software engineer AIs right now include Asana, Block, and Cribl, based on current remote listings on Migrate Mate as of September 2026. Remote-first firms, AI product startups, and distributed engineering teams at larger technology and fintech companies account for the bulk of these openings.
Can you get a remote software engineer AI job with no experience?
Yes, but remote entry-level AI roles are harder to land because employers expect you to ramp up with minimal hand-holding. What opens the door is a concrete portfolio: personal projects, Kaggle competition results, or open-source contributions that show you can build and ship AI work independently. AI-native startups and smaller distributed teams are the most likely to hire junior engineers into remote roles.
Do you need a degree for remote software engineer AI jobs?
Not always. Many remote employers care more about what you've built and deployed than where you studied. A strong GitHub repository, documented model performance, and experience with production ML pipelines carry significant weight. That said, roles at larger companies or those requiring security clearances often list a degree as a formal requirement, so it depends on the employer.
Which industries hire the most remote software engineer AIs?
Remote software engineer AI roles concentrate in Technology & Software, Consulting & Professional Services, and Education, based on current remote listings on Migrate Mate as of September 2026. These sectors rely on distributed engineering teams and invest heavily in AI product development, making remote hiring a standard practice rather than an exception.
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