Trase Systems is seeking a Staff Software Engineer to split their time between building the core product and delivering solutions to customers. You will embed with customer teams to understand workflows, data environments, and operational constraints, then design and deploy production-quality systems that solve real problems. This is a remote-friendly role based in the United States (with potential to base from McLean, VA or Seattle, WA), and you will own delivery from prototype through production, write code, debug across applications and infrastructure, and help shape platform architecture by turning field learnings into reusable capabilities and roadmap updates. You will work with product, security, and customer teams to ensure secure, reliable, auditable, and operationally useful solutions. You should be comfortable translating vague requirements into concrete technical plans and communicating clearly with engineers, product teams, executives, and customer stakeholders. Requirements include 8+ years of software engineering experience, experience applying AI/ML techniques (including LLM-based approaches such as RAG, guardrails, and evals), scalable system design, and experience with backend services, distributed systems, data pipelines, cloud infrastructure, or applied AI/ML systems. Comfort working across the full stack is expected, along with the ability to operate in ambiguous customer environments. Preferred qualifications include experience with AI agents, workflow orchestration, model deployment, cloud platforms (AWS, Azure, GCP), Kubernetes, Terraform, Docker, CI/

Trase Systems is seeking a Staff Software Engineer to split their time between building the core product and delivering solutions to customers. You will embed with customer teams to understand workflows, data environments, and operational constraints, then design and deploy production-quality systems that solve real problems. This is a remote-friendly role based in the United States (with potential to base from McLean, VA or Seattle, WA), and you will own delivery from prototype through production, write code, debug across applications and infrastructure, and help shape platform architecture by turning field learnings into reusable capabilities and roadmap updates. You will work with product, security, and customer teams to ensure secure, reliable, auditable, and operationally useful solutions. You should be comfortable translating vague requirements into concrete technical plans and communicating clearly with engineers, product teams, executives, and customer stakeholders. Requirements include 8+ years of software engineering experience, experience applying AI/ML techniques (including LLM-based approaches such as RAG, guardrails, and evals), scalable system design, and experience with backend services, distributed systems, data pipelines, cloud infrastructure, or applied AI/ML systems. Comfort working across the full stack is expected, along with the ability to operate in ambiguous customer environments. Preferred qualifications include experience with AI agents, workflow orchestration, model deployment, cloud platforms (AWS, Azure, GCP), Kubernetes, Terraform, Docker, CI/