Senior Applied AI Systems Engineer

JFDI Accountants is a global leader in crypto accounting that serves influential players in the industry. They are seeking a Senior Applied AI Systems Engineer to support the development and maintenance of their custom software platform, focusing on AI-enabled workflows and production-grade software systems.

Responsibilities:

• Design and evolve internal software platforms, agentic workflows, and business tools that solve real operational problems
• Orchestrate solutions across front-end, back-end, database, API, and AI tooling layers, including model and tool integrations
• Define, review, and refine AI-generated and human-written code for quality, maintainability, security, and alignment with engineering standards
• Own the software delivery lifecycle from requirements and architecture through deployment, monitoring, and iteration
• Investigate failures across software and AI systems, debug workflow issues, and implement durable improvements
• Build and refine evaluation harnesses, regression tests, and acceptance criteria for AI-driven and traditional software changes
• Integrate internal systems with third-party platforms, LLM providers, data sources, and workflow tools
• Ensure applications and AI workflows are performant, secure, observable, cost-aware, and maintainable
• Establish guardrails, review processes, technical documentation, and deployment patterns that keep AI-assisted delivery reliable and auditable
• Work closely with internal stakeholders to identify workflow bottlenecks, automation opportunities, and high-value AI use cases
• Partner with the Director of Engineering and CEO on technical priorities, architecture decisions, and execution plans
• Communicate architecture choices, model tradeoffs, and delivery risks clearly to non-technical stakeholders
• Contribute to a culture of accountability, experimentation, pragmatic delivery, and high engineering standards

Requirements:

• Minimum 4+ years of software engineering experience with strong hands-on architecture, delivery, and code review ability
• Experience delivering production systems across application, API, data, and infrastructure layers
• Experience building business applications, internal tools, APIs, workflow systems, and AI-assisted processes
• Experience designing AI workflows, tool-calling systems, evaluation harnesses, or human-in-the-loop review processes
• Strong understanding of SDLC, software design, testing strategy, maintainable architecture, and secure software development
• Ability to evaluate models and tools based on quality, latency, cost, reliability, safety, and operational fit
• Experience with cloud platforms such as Azure and/or AWS, CI/CD pipelines, DevOps workflows, and containerization (e.g., Docker)
• Experience working within a Microsoft-stack environment preferred
• Ability to move from business requirements to architecture, rollout plans, and production operations
• Ability to work independently while collaborating with cross-functional teams and executive stakeholders
• Strong written and verbal communication skills, including the ability to explain technical tradeoffs clearly
• Familiarity with blockchain, cryptocurrency, or financial/accounting systems is a plus
• C# / .NET / .NET Core for production application development
• API development, integrations, and tool interfaces, including RESTful services
• Relational databases, data modeling, and query optimization, including Microsoft SQL Server and/or MySQL
• ORMs such as Entity Framework, Dapper, or similar tools
• Source control platforms such as Git and AI-assisted development workflows
• Software testing methodologies, including unit, functional, integration, and regression testing
• CI/CD pipelines, deployment workflows, and release automation
• Application architecture, software design principles, and cloud infrastructure fundamentals
• LLM/AI integration patterns, model/tool selection, prompt workflows, and evaluation/tracing practices
• Debugging, troubleshooting, observability, and technical documentation across the development lifecycle