This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Staff Software Engineer – Builder Platform based in United States.
As a Senior Staff Software Engineer, you will provide company-wide technical leadership, shaping the long-term vision and architecture of an advanced internal platform focused on AI agents, automated workflows, and developer productivity. You will lead strategic initiatives spanning AI infrastructure, platform engineering, developer tools, and productivity engineering. Working across multiple engineering teams and business functions, you will establish scalable architectural standards, governance frameworks, and best practices that accelerate innovation while maintaining security, reliability, and cost efficiency. You will drive the adoption of AI-powered technologies and build the infrastructure that enables teams to automate complex engineering and business processes. This role combines deep technical expertise, strategic thinking, and organizational influence, offering the opportunity to shape how an entire company builds, deploys, and operates software. You will also mentor senior technical leaders and contribute to open-source solutions with broader industry impact.
Accountabilities:
- Technical Vision and Strategic Leadership: Define and communicate the multi-year technical vision for the Builder Platform, translating organizational strategy into a clear roadmap covering AI agents and workflows, AI infrastructure, developer infrastructure, and productivity engineering.
- Lead major cross-functional technical initiatives, ensuring alignment between engineering teams, business stakeholders, and organizational priorities.
- Establish architectural standards, technical principles, and clear ownership boundaries that support sustainable platform development and adoption.
- Agent Platform and AI Infrastructure: Lead the architecture, development, and evolution of the shared Agent Platform, enabling teams to deploy, operate, evaluate, govern, and continuously improve AI agents and automated workflows.
- Design and operate centralized Large Language Model (LLM) and Model Context Protocol (MCP) gateways, establishing appropriate guardrails, fallback mechanisms, usage monitoring, cost controls, model rollout policies, and Service Level Objectives (SLOs).
- Implement AI governance frameworks in collaboration with Security, Legal, and IT teams, translating organizational policies into practical controls, approved usage patterns, and auditable processes.
- Architect intelligent agents and workflows that automate engineering activities from issue identification to production deployment, as well as business processes from initial triggers to measurable outcomes.
- Determine which agentic capabilities should become standardized platform services and which should remain independently managed by individual teams.
- Developer Infrastructure and Productivity Engineering: Own the technical strategy for developer infrastructure, including source control systems, Continuous Integration (CI), repository standards, access management, ownership models, and reusable workflows.
- Improve CI reliability, infrastructure efficiency, and developer experience by reducing friction and optimizing engineering processes.
- Define and implement standardized approaches to agentic development tools, including best practices, reusable workflows, enablement resources, and internal adoption strategies.
- Drive organization-wide adoption of AI-powered coding tools and agentic technologies through collaboration, influence, and practical enablement rather than rigid mandates.
- Cross-Functional Collaboration and Governance: Partner with senior stakeholders across Engineering, Product, Sales, and General and Administrative (G&A) functions to identify opportunities where AI and automation can improve business outcomes.
- Prioritize strategic initiatives into a coordinated company-wide technical portfolio.
- Define which capabilities should be centralized, standardized, delegated to individual teams, purchased externally, or deliberately excluded from development.
- Balance speed, flexibility, reliability, security, cost, and long-term maintainability when making complex architectural and organizational decisions.
- Establish governance through standardized tools, approved workflows, and practical implementation patterns that encourage adoption without creating unnecessary bureaucracy.
- Performance Measurement and Continuous Improvement: Define outcome-oriented metrics to measure platform adoption, engineering velocity, reliability, quality, and infrastructure costs.
- Establish feedback loops that quantify productivity improvements and provide actionable insights for roadmap prioritization.
- Use performance data and stakeholder feedback to identify systemic issues and continuously improve platform capabilities.
- Product Strategy and Open-Source Contributions: Lead the internal customer-zero strategy, using real organizational implementations to validate platform capabilities and identify opportunities for product improvement.
- Translate internal experience into validated technical requirements for cloud products, software development kits (SDKs), and agent development frameworks.
- Maintain a continuous feedback loop with product leadership to influence product strategy and development priorities.
- Lead the development of open-source reference architectures that customer platform teams can adopt.
- Represent the organization's technical strategy with customers, partners, and the broader engineering community.
- Technical Leadership and Mentorship: Develop senior technical leaders and strengthen collaboration among engineering leads, managers, and individual contributors.
- Influence organizational effectiveness through architectural clarity, mentorship, consensus building, and technical guidance rather than relying on direct reporting authority.
- Participate in the on-call rotation while proactively driving systemic improvements that reduce operational overhead, mitigate risks, and enhance the internal developer experience.
Requirements:
- Strong software engineering fundamentals, with a proven track record of setting technical direction and delivering major platform initiatives across multiple engineering teams.
- Extensive experience building, scaling, and operating internal platforms, developer infrastructure, AI platforms, or agent ecosystems adopted across an organization.
- Hands-on experience with modern agentic coding tools such as Codex and Claude Code, including establishing company-wide best practices and successfully driving adoption.
- Proficiency in at least one programming language commonly used in modern engineering environments, such as Go, TypeScript/JavaScript, Python, or Java.
- Deep technical expertise in at least one relevant domain, such as developer infrastructure, distributed systems, AI platforms, or platform engineering, alongside strong working knowledge of several related areas.
- Demonstrated ability to design scalable architectures and make complex technical decisions involving reliability, security, cost optimization, flexibility, and long-term maintainability.
- Strong judgment in defining platform boundaries, including deciding which capabilities should be centralized, standardized, federated, purchased, or intentionally not developed.
- Experience translating ambiguous organizational objectives into technical strategies, architectural standards, roadmaps, and coordinated execution plans.
- Proven ability to influence and align engineering managers, senior individual contributors, Security, Legal, IT, Product, and business stakeholders.
- Experience defining and implementing governance frameworks through practical tools, standardized workflows, and approved development patterns rather than documentation or approval processes alone.
- Ability to establish measurable success criteria for developer productivity and AI systems, including adoption, reliability, quality, cost, and development cycle time.
- Strong analytical and strategic thinking skills, with the ability to use data and qualitative feedback to guide technical investments and organizational priorities.
- Excellent written and verbal communication skills, particularly in producing technical documentation, defining architectural strategies, and communicating complex concepts to diverse audiences.
- Demonstrated leadership in mentoring senior engineers and technical leaders, building consensus, and improving the effectiveness of multiple teams.
- Ability to operate effectively in complex, cross-functional environments while balancing strategic planning with hands-on technical leadership.
- Preferred Qualifications:
- Experience building internal AI agents and designing or operating enterprise-wide agent platforms.
- Experience developing and operating applications using Temporal or comparable workflow orchestration technologies.
- Previous involvement in defining or implementing AI governance frameworks, model-access infrastructure, or agent evaluation systems.
- Experience managing GitHub configurations, organizational policies, repository standards, and workflows at scale.
- Familiarity with developer productivity measurement frameworks, including SPACE and DORA metrics.
- Experience contributing to open-source projects or developing reusable technical reference architectures.
- Background in platform engineering, infrastructure strategy, or developer experience within a growing technology organization.
Benefits:
- Competitive compensation: Senior-level compensation based on experience, technical expertise, job level, and geographic location.
- Annual salary ranges (USD, published reference):
- Tier 1: $260,000 – $341,250.
- Tier 2: $234,000 – $307,125.
- Tier 3: $208,000 – $273,000.
- Equity opportunities: Compensation packages include equity opportunities, allowing eligible employees to participate in the organization's long-term growth.
- Fully remote work: Work remotely from United States, with flexibility and autonomy.
- Strategic technical ownership: Shape the long-term technical direction of an organization-wide platform and influence major engineering decisions.
- Advanced technology exposure: Work with cutting-edge AI infrastructure, agentic systems, distributed workflows, and modern developer platforms.
- Professional growth: Expand your expertise in AI governance, platform engineering, infrastructure architecture, and enterprise-scale automation.
- Leadership opportunities: Mentor senior engineers, develop technical leaders, and influence engineering practices across multiple teams.
- Open-source impact: Contribute to open-source architectures and tools designed to benefit the wider technology community.
- Collaborative environment: Work with multidisciplinary teams across Engineering, Product, Security, Legal, IT, and business functions.
- Inclusive workplace: Join an equal opportunity organization that values diversity, accessibility, individual contributions, and different perspectives.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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