Senior Software Engineer
Brandt Information Services. LLC · Remote · remote
Senior Software Engineer
Must be US Citizen or Green Card holder
Full-Time Salaried Position
Remote Work Within the Continental United States
About Brandt
Brandt is the get-outdoors company. State and local agencies steward the parks, lakes, and wildlife people come for; our platforms make getting there easy — from purchasing a hunting or fishing license, to registering a boat, to reserving a campsite — and help agencies manage those resources sustainably. A family with a trip planned doesn’t get a second try at opening day, and neither do we. We're modernizing our platform and building new products, always with an eye toward making that experience better for the agencies and the people who depend on it.
Learn more about Brandt at .
Where You Fit
Brandt’s engineering organization spans Licensing, Registrations, and Reservations, the platforms agencies rely on to run camping, hunting, fishing, and boating programs at scale, along with the services layer around them (fulfillment, CRM, contact center, and more).
This opening is not tied to a single product team or technology platform. It is a cross-cutting role focused on applying AI to how we build and run software: building agentic systems, AI-assisted development workflows, and the tooling that helps engineering teams ship faster and with higher quality. As Senior Software Engineer, you build and ship that work hands-on, within the architecture and technical standards set by our Principal engineers and Chief Engineer, and you help those standards improve by bringing back what you learn in the code.
This role is for strong, self-directed engineers: the kind who take a loosely defined problem and run with it without close oversight. Engineers on our IC track are expected to bring strength that travels. While this role is anchored on AI-enabled engineering today, you may be asked to contribute across Licensing, Registrations, Reservations, or emerging initiatives as business needs shift, picking up new domains quickly rather than needing years to ramp on one narrow system.
And you care about the mission. The tools and systems you build here don’t exist for their own sake. They help us put better software in the hands of the agencies and people who depend on it, which gets more people outdoors and funds the conservation work that keeps those spaces open. That’s not incidental to the engineering work; it’s the point.
The Role
This is a senior individual contributor role, for engineers who want to stay close to the code and own meaningful pieces of the work from design through production. You’re not here to manage a team; we have dedicated Engineering Managers and Tech Leads for that. You’re here to design and build high-leverage systems yourself, including the AI-enabled systems and agents that change how our teams work, within the architecture and standards the rest of engineering builds on.
Systems thinking is part of the job: you look past the immediate task to the broader pattern, and you flag when something you’re building could help other teams. You don’t need a fully specified spec to make progress. You can take a loosely defined problem, shape it into a plan, and check in at the right moments rather than constantly.
You’ll turn ambiguous problems into shipped, production-grade systems, with the judgment to know when to move fast and when to slow down. AI is central to that judgment: you build with it, you build for it, and you know where to trust its output and where to verify it yourself.
You’ll influence the people around you through the quality of your work, your reviews, and your willingness to share what you learn, not through formal authority.
This is also a fully remote role, not a hybrid arrangement with an office waiting for you to return to. There’s no relocation clause in the fine print and no plan to change that as the team grows. You build your work around deep, focused engineering time instead of a commute, permanently, not as a temporary accommodation.
Responsibilities
- Design, develop, and deliver complex technical solutions, including AI-enabled and agentic systems, that meet functional, performance, and security requirements
- Build production-grade agents and AI-powered workflows, including tool use, orchestration, retrieval, and integration with existing systems of record
- Translate loosely defined business and product requirements into a clear technical plan and execute against it
- Write high-quality, maintainable, testable code, and own the components you build from design through production
- Use AI coding assistants and agentic coding tools daily, apply the team’s AI practices, and bring back what works and what doesn’t so those practices improve
- Build evaluation, testing, and observability for the AI behavior you ship so quality is measured rather than assumed
- Apply AI across the delivery lifecycle, from discovery and requirements through build, test, release, and support, and help measure the effect on speed and quality
- Build safe interfaces, adapters, and guardrails that let agents work against legacy and long-lived systems
- Participate in code reviews and design reviews, giving and receiving feedback that raises the quality of the team’s work
- Collaborate across product, architecture, QA, and DevOps to ensure end-to-end delivery quality, and uphold strong engineering standards and CI/CD discipline
- Identify technical risks and dependencies early and raise them, including AI-specific risks such as security, data privacy, cost, and reliability
- Evaluate emerging models, tools, and techniques and recommend what fits the problem, staying model- and vendor-agnostic
- Work across product domains (Licensing, Registrations, Reservations, and beyond) as business priorities shift
Tech Stack & Experience
- 7+ years of hands-on software engineering experience, including ownership of significant components or features from design through production
- You work in a highly agentic way today. AI coding agents are central to how you build, and you know when to trust their output and when to verify it yourself
- You’ve built your own agents, automations, or tooling to make yourself or your team faster, such as custom agent workflows, MCP servers, or scripts that chain models and tools together. Side projects and internal tools count
- Working knowledge of how agents work under the hood: tool use, orchestration, context management, and structured outputs
- A habit of checking AI output rather than assuming it’s right, whether through tests, review, or lightweight evals
- Awareness of AI security and data-handling risks, including prompt injection, data leakage, and access control for agents
- Strong foundation in at least one modern programming language and the ability to pick up others quickly; we value engineering depth and fast learning over loyalty to a specific stack
- RESTful APIs, service-oriented or microservice architectures, and at least one major cloud platform (e.g., Azure, AWS, GCP)
- Relational databases and data modeling
- DevOps practices and CI/CD tooling, with experience automating build, test, and release pipelines
- Experience working in, or integrating with, legacy and long-lived systems
- Nice to have: Experience building LLM-powered features into products, including retrieval-augmented generation, evals, production monitoring of AI behavior, and vector or search stores
- Nice to have: containerization (Docker, Kubernetes), Model Context Protocol (MCP) or similar tool-integration standards, front-end experience with a modern framework, contributions to open-source projects or technical writing
- No specific industry background is required. We care how quickly you learn a new domain, not which one you came from
Compensation & Benefits
The selected candidate should have the skills, qualifications, and experience consistent with a Senior I level within Brandt’s job architecture. The compensation range is $13