Senior AI-Driven Software Engineer: Multi-Agent Coding
Listed on 2026-05-27
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Software Development
AI Engineer, Software Engineer, Machine Learning/ ML Engineer, Data Scientist
Mark
43 is approved to hire in Canada, the UK, and 40 U.S states, includingAZ, CA-excluding San Francisco, CO, CT, DC, FL, GA, IA, IL, IN, KS, MA, MD, ME, MI, MO, NE, NJ, NM, NY, NC, OH, OR, PA, SC, TN, TX, UT, VA, VT, WA, and WI.Before applying to a remote role, please ensure that you are able to perform the position in one of the states listed above.
State locations and specifics are subject to change as our hiring requirements shift.
Applicants must be authorized to work for any employer in the country in which the role is being hired. We are unable to sponsor or take over sponsorship of an employment visa at this time.
Senior Software Engineer – AI-Enabled Engineering
Mark
43’s mission is to empower communities and their governments with new technologies that improve the safety and quality of life for all. We build powerful, scalable, and elegant software that sets a new standard for the tools upon which our first responders rely. Our users are diverse, and we are therefore committed to embracing diversity of thought and experience within our team.
Our platform is already trusted by major public safety agencies across North America—including Boston, D.C., Seattle, and the California Highway Patrol—and we’ve recently expanded into the UK with our first customer overseas.
Now, we’re entering an exciting new chapter: Mark
43 is building a next-generation AI-augmented engineering team. This is a foundational opportunity to help rethink how software is designed, developed, and delivered using intelligent agentic or related tools.
What You’ll Do
We’re looking for a Senior Software Engineer to help lead our AI-enabled engineering initiative. You’ll work at the frontier of AI and software development, experimenting with agentic workflows and shaping how AI tools are integrated into every layer of our engineering stack.
This isn’t just about using AI to autocomplete code—it’s about designing and orchestrating systems of AI agents that can plan, write, review, test, and deploy software collaboratively. In essence, you’ll play a role akin to a tech lead for a team of intelligent coding agents.
You will:
- Design multi-agent systems with coding-focused agents (e.g., code writer, reviewer, tester, deployer)
- Write the prompts, logic, and scaffolding that guide each agent’s behavior
- Handle tool use, like enabling agents to access the file system, test runners, version control, and internal APIs
- Evaluate and refine agents’ output, performance, collaboration patterns, and feedback loops
If you were on the team last week, you might have:
- Prototyped a new coding assistant workflow using open-source LLMs and internal knowledge bases
- Led an architecture discussion on agentic build pipelines or automated PR generation
- Collaborated with a cross-functional team to build a fast, AI-powered interface for internal tooling
- Helped define the evaluation framework for AI contributions—accuracy, speed, and impact
- Mentored a teammate on combining Type Script and AI tools to accelerate UI prototyping
- Explored best practices for safely and securely integrating generative AI into a public sector codebase
What You’ll Need
We’re looking for an experienced software engineer who is eager to build smarter systems by pairing technical expertise with emerging AI tools. You don’t need to be an AI researcher—but you do need hands-on experience applying generative AI tools to real-world development workflows.
You should have:
- 5+ years of professional software engineering experience
- Proficiency with at least part of our stack:
Java, Type Script + React, and MySQL
- Extensive applied experience with AI-assisted development tooling—whether it’s Cursor, Windsurf, LLM APIs, codegen platforms, vector databases, agentic frameworks like Lang Chain, or custom-built systems
- A strong product mindset and interest in building for real-world impact
- A bias toward experimentation, iteration, and continuous learning
- Comfort operating in ambiguity and helping define best practices in a rapidly evolving space
We’re flexible on which tools you’ve used—we care more about your ability to learn, adapt, and creatively apply AI in practical settings than checking a specific tech box.
People…
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