Staff Software Engineer (Product + Platform Development)

About the Role

We are hiring a Staff Software Engineer who will split their time between building our core product and delivering it directly to customers. This role sits at the intersection of software engineering, product development, customer delivery, and operational execution.

You will embed with customer teams to understand their workflows and highest-value use cases, then build production-ready systems that solve real problems. Just as importantly, you will feed what you learn in the field back into the core product, shaping platform capabilities, reusable patterns, and roadmap so that each deployment makes the next one faster. You will move quickly from discovery to prototype to deployment while maintaining the engineering discipline required for secure and regulated environments.

This is a hands-on, senior engineering role. As a Staff engineer, you will set technical direction, make key architecture decisions, and raise the bar for how we build, while still writing code, debugging systems, and working through messy customer environments yourself. You should be comfortable translating vague requirements into concrete technical plans and communicating clearly with both engineers and non-technical stakeholders.

What You’ll Do

• Work directly with customers to understand their workflows, pain points, data environments, and operational constraints.
• Contribute to both the core platform and customer-specific integrations: build reusable capabilities into the product, then adapt and deploy them in each customer's environment.
• Build and deploy AI-enabled applications, agents, and workflow automation, applying AI/ML and LLM techniques such as RAG, guardrails, and evals to deliver reliable customer solutions.
• Translate customer needs into technical requirements, implementation plans, and product feedback for the core engineering team.
• Own delivery from prototype through production, including architecture, backend services, APIs, integrations, observability, testing, deployment, and customer acceptance.
• Integrate with customer systems, data sources, identity providers, and cloud or on-prem infrastructure.
• Partner with product, engineering, security, and customer teams to ensure solutions are secure, reliable, auditable, and operationally useful.
• Debug issues in deployed environments and drive fast resolution across application, infrastructure, data, and integration layers.
• Operate with strong judgment in environments involving sensitive data and business-critical workflows.

Requirements

• 8+ years of software engineering experience, with a strong foundation in building and shipping production-quality systems.
• Ability to apply AI and ML techniques, including LLM-based approaches such as RAG, guardrails, and evals, to real customer problems.
• Scalable system design experience, ensuring solutions scale reliably as usage, data, and complexity grow.
• Experience with backend engineering, distributed systems, APIs, data pipelines, cloud infrastructure, or applied AI/ML systems.
• Comfort working across the full stack when needed, including backend services, frontend interfaces, infrastructure, integrations, and deployment workflows.
• Ability to operate in ambiguous customer environments and turn unclear requirements into working software.
• Strong technical communication skills with engineers, product teams, executives, and customer stakeholders.
• High ownership, bias for action, and ability to drive outcomes without waiting for perfect requirements.
• Strong debugging instincts and ability to reason across application code, data, infrastructure, networking, and customer systems.

Preferred Qualifications

• Prior experience as a full-stack or backend software engineer, forward deployed engineer, solutions engineer, product engineer, platform engineer,, or founding/startup engineer.
• Experience with AI agents, LLM applications, workflow orchestration, evals, guardrails, retrieval systems, or model deployment.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with Kubernetes, Terraform, Docker, CI/CD, observability, and secure deployment practices.
• Familiarity with identity and access management, audit logging, data governance, and secure software delivery.
• Experience building in environments with compliance, security, or operational constraints.
• Comfort working in secure or regulated customer environments.

If you want to be on the cutting edge of technology, building AI solutions for the future, and are up for a challenge, let’s talk!

Salary Range: $180,000-240,000. This represents the typical salary range for this position based on experience, skills, and other factors.

Some travel to customers may be required.