Lead Engineer - AI Trust & Governance

We are seeking a highly skilled, hands-on, and deeply technical Software Development Engineer to help build our AI Governance platform from the ground up. This is a critical senior role responsible for designing and developing both the front-end and back-end foundations of a platform that enables safe, trusted, and scalable AI deployment across the enterprise.

This role will directly support our number one value:
Trust.

You will help architect and deliver a platform that spans governance, intake workflows, lifecycle management, monitoring, observability, risk controls, and operational tooling for AI systems and agents. We are looking for a builder who is comfortable wearing multiple hats across software engineering, cloud infrastructure, platform engineering, developer tooling, and user experience.

• Full Stack Platform Development:
  Lead the end-to-end design, development, and scaling of the AI governance platform, building both the front-end and back-end components that support enterprise-wide AI governance.
• AI-Assisted Engineering:
  Use AI development tools such as Claude and other coding assistants as part of the software development lifecycle to accelerate delivery, improve code quality, prototype faster, and enhance engineering productivity.
• AWS Cloud Infrastructure Development:
  Design and build secure, scalable, and resilient cloud native infrastructure on AWS to support platform services, governance workflows, system integrations, and application performance at enterprise scale.
• ML and AI Platform Services:
  Build and support platform capabilities that enable AI and machine learning systems to be governed, monitored, tracked, and managed throughout their lifecycle, including services that support model and agent operations.
• CI/CD Delivery Process Knowledge:
  Bring practical knowledge of CI/CD concepts, automated testing, and deployment workflows, and release management practices to help ensure the platform can be delivered reliably across environments.
• Architecture and Technical Design:
  Define and drive the overall platform architecture, including service design, API strategy, data flows, integration patterns, event-driven workflows, and system scalability considerations.
• Monitoring and Operational Visibility:
  Develop monitoring capabilities that provide insight into system health, application performance, workflow execution, service reliability, and platform usage across the governance ecosystem.
• Observability and Telemetry:
  Build observability components that capture logs, metrics, traces, and runtime telemetry across platform services, enabling deeper diagnostics, issue detection, root cause analysis, and ongoing operational intelligence.
• Generative AI Platform Development:
  Assist with designing and developing Generative AI capabilities as part of the platform, including LLM powered features, intelligent workflows, agent-based functionality, and other AI native applications.
• Technical Leadership and Ownership:
  Provide strong technical leadership across the stack, establish engineering standards, influence design decisions, mentor other engineers, and take ownership of delivering a strategic platform from the ground up.
• Cross Functional
  
  Collaboration:
  
  Partner closely with product, architecture, security, compliance, governance, and engineering stakeholders to translate business goals and trust requirements into scalable technical solutions.

• 10+ years of professional software development experience with significant depth across both front-end and back-end development.
• Strong hands-on expertise in full stack development, including modern front-end frameworks, API design, distributed systems, and back-end application development.
• Proven experience building complex platforms or enterprise applications from scratch.
• Deep experience with AWS and cloud-native architecture, including designing scalable, secure, and production-grade systems.
• Strong experience with platform engineering, developer infrastructure, and production software delivery practices.
• Demonstrated ability to build and scale CI/CD pipelines, automated frameworks, and deployment workflows.
• Experience building systems with strong monitoring, observability, logging, telemetry, and operational insight capabilities.
• Strong architectural judgment.
• Experience working in environments where security, compliance, governance, and auditability are important design considerations.
• Comfort working across ambiguity and leading technical execution in highly visible, high-impact initiatives.
• Excellent collaboration and communication skills.
• Demonstrated experience using Generative AI as part of the software development lifecycle.

• Experience with Salesforce Ecosystem.
• Experience building or supporting AI governance, model governance, risk, trust, compliance, or observability platforms.
• Experience with Gen AI applications, LLM-powered systems, agentic workflows, and model evaluation frameworks.
• Experience with MLOps, LLMOps, or AI…