Staff Software Engineer, Go-to-Market Systems & AI

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer, Go-to-Market Systems & AI based in the United States. This is a high-impact Staff-level engineering role focused on transforming how sales teams operate through scalable systems, automation, and AI-powered experiences. You will own the technical strategy and long-term architecture of a critical go-to-market technology stack. The role combines hands-on software engineering with technical leadership, allowing you to shape solutions from early prototypes through production operations. You will work closely with Sales, Strategy & Operations, Product, Data, and Engineering leaders to solve complex business problems and improve productivity. A major focus will be building reliable AI agents and automated workflows that reduce manual effort and enable better, faster decision-making. You will also establish the standards, evaluation frameworks, security practices, and guardrails needed to deploy AI safely with sensitive business data. This is an opportunity to influence engineering direction at scale while remaining deeply involved in the technology and mentoring other engineers.

Accountabilities

• Own the technical strategy, architecture, and long-term evolution of the go-to-market systems and technology stack.
• Design, build, deploy, and operate production-grade AI agents and automated workflows that reduce manual sales activities, improve decision-making, and increase sales productivity.
• Lead technical execution across initiatives of varying complexity by establishing direction, breaking down ambiguous problems, reviewing designs, and supporting engineers in delivering high-quality solutions.
• Remain hands-on throughout the complete software development lifecycle, including prototyping, architecture, implementation, testing, deployment, monitoring, and production operations.
• Partner with Sales and Sales Strategy & Operations to understand workflows, identify high-value opportunities, and translate business challenges into scalable technical solutions.
• Establish engineering patterns, evaluation methodologies, and guardrails for AI systems that are reliable, observable, secure, and appropriate for handling sensitive business information.
• Define success metrics and use data, evaluations, and user feedback to continuously improve the accuracy, adoption, reliability, and business impact of new capabilities.
• Make informed build-versus-buy decisions and lead integrations across internal platforms, CRM systems, data services, and third-party technologies.
• Build alignment with senior technical and business stakeholders while communicating complex architectural decisions, risks, and tradeoffs clearly.
• Raise engineering standards through mentorship, architecture guidance, technical reviews, and direct contribution to critical projects.
• Help determine when AI models, deterministic software, or human oversight should be used to deliver effective and responsible solutions.

Requirements

• Minimum of 12 years of related professional experience with a Bachelor’s degree, 8 years with a Master’s degree, 5 years with a PhD, or equivalent professional experience.
• Proven experience setting technical direction and delivering complex, business-critical systems across multiple teams or functional areas.
• Strong experience designing, building, and operating production software incorporating large language models, AI agents, tool calling, retrieval, workflow orchestration, or related AI technologies.
• Demonstrated ability to take AI capabilities from prototype through production, including evaluation, observability, security, reliability, and appropriate human oversight.
• AI-native engineering mindset, with experience using AI tools throughout the development lifecycle while exercising sound judgment about when to use AI models, deterministic systems, or human review.
• Excellent software engineering and system design capabilities, with the ability to work hands-on across application, service, integration, and data layers.
• Strong technical leadership skills demonstrated through influence, mentorship, architecture, design reviews, and direct engineering contribution rather than formal reporting authority.
• Strong judgment and problem-solving ability, with the capacity to navigate ambiguity, assess technical and business tradeoffs, and influence sen…