Confluent
Principal Engineer, Engineering AI Productivity
Rol remoto de Engineering con fit claro de ubicación del candidato.
Publicado13 may 2026
Países elegibles1 país aceptado
Señal de seniorityLead
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Estados Unidos
Resumen del rol
Principal Engineer, Engineering AI Productivity
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
What You Will Do:
- Strategy & VisionDefine and evangelize the AI and agentic flows strategy — aligning business metrics, engineering needs, and platform opportunities.Build a roadmap for introducing agentic automation features, smart assistants, and AI-driven workflows across all aspects of engineering.Identify and resolve bottlenecks across the entire product and software development life cycle.
- Define and evangelize the AI and agentic flows strategy — aligning business metrics, engineering needs, and platform opportunities.
- Build a roadmap for introducing agentic automation features, smart assistants, and AI-driven workflows across all aspects of engineering.
- Identify and resolve bottlenecks across the entire product and software development life cycle.
- Cross-Functional LeadershipPartner with Engineering, Trust and Security to integrate AI capabilities responsibly and at scale.Operationalize AI adoption internally and share use cases externallyDrive complex cross-team projects requiring multi-stakeholder alignmentContinuously raise the bar for code/architectural quality across engineering
- Partner with Engineering, Trust and Security to integrate AI capabilities responsibly and at scale.
- Operationalize AI adoption internally and share use cases externally
- Drive complex cross-team projects requiring multi-stakeholder alignment
- Continuously raise the bar for code/architectural quality across engineering
- Execution & DeliveryLead the delivery of core agentic workflows that improves productivity across engineeringBalance of hands-on contributions with effective delegation to others. Expect 60% execution and 40% strategy setting.Drive measurable adoption of AI tooling and flows with internal teams
- Lead the delivery of core agentic workflows that improves productivity across engineering
- Balance of hands-on contributions with effective delegation to others. Expect 60% execution and 40% strategy setting.
- Drive measurable adoption of AI tooling and flows with internal teams
- Governance & Best PracticesAbility to adopt industry standards, ethical frameworks, guardrails, and quality metrics for AI behavior and automated flows.Define success metrics and KPIs (e.g., AI-driven usage lift, automation ROI, reduction in manual workflows).
- Ability to adopt industry standards, ethical frameworks, guardrails, and quality metrics for AI behavior and automated flows.
- Define success metrics and KPIs (e.g., AI-driven usage lift, automation ROI, reduction in manual workflows).
- Thought LeadershipParticipate in external forums — conferences, podcasts, customer briefings on occasionEvolve as the technology landscape shiftsWrite internal playbooks for building and scaling agentic outcomes.
- Participate in external forums — conferences, podcasts, customer briefings on occasion
- Evolve as the technology landscape shifts
- Write internal playbooks for building and scaling agentic outcomes.
Details
- Define and evangelize the AI and agentic flows strategy — aligning business metrics, engineering needs, and platform opportunities.
- Build a roadmap for introducing agentic automation features, smart assistants, and AI-driven workflows across all aspects of engineering.
- Identify and resolve bottlenecks across the entire product and software development life cycle.
- Partner with Engineering, Trust and Security to integrate AI capabilities responsibly and at scale.
- Operationalize AI adoption internally and share use cases externally
- Drive complex cross-team projects requiring multi-stakeholder alignment
- Continuously raise the bar for code/architectural quality across engineering
- Lead the delivery of core agentic workflows that improves productivity across engineering
- Balance of hands-on contributions with effective delegation to others. Expect 60% execution and 40% strategy setting.
- Drive measurable adoption of AI tooling and flows with internal teams
- Ability to adopt industry standards, ethical frameworks, guardrails, and quality metrics for AI behavior and automated flows.
- Define success metrics and KPIs (e.g., AI-driven usage lift, automation ROI, reduction in manual workflows).
- Participate in external forums — conferences, podcasts, customer briefings on occasion
- Evolve as the technology landscape shifts
- Write internal playbooks for building and scaling agentic outcomes.
- 8+ years driving strategic productivity initiatives, ideally in SaaS/Cloud platforms or developer tools with some proven experience in AI initiatives.
- Considered an expert in building distributed systems and/or the infrastructure and tools to support it.
- Proven ability to lead cross-functional teams and influence senior stakeholders without direct authority.
- Strong communicator who can translate complex technical strategies into impact-oriented outcomes.
- Demonstrated track record delivering products or features that generated measurable business value.
- Comfortable defining success criteria, metrics, and ROI for ambiguous, future-facing domains.
- Hands-on experience with AI or adjacent AI/ML platform experience with LLM integration and workflow automation, with demonstrated appetite to build toward agentic patterns
- Deep understanding of responsible AI practices and governance.
- Passion for solving real customer problems with elegant, scalable solutions.
- Ability to tie technical efforts directly to business KPIs (adoption, retention, revenue impact).
What You Will Bring:
- Technical and Product Acumen8+ years driving strategic productivity initiatives, ideally in SaaS/Cloud platforms or developer tools with some proven experience in AI initiatives.Considered an expert in building distributed systems and/or the infrastructure and tools to support it.
- 8+ years driving strategic productivity initiatives, ideally in SaaS/Cloud platforms or developer tools with some proven experience in AI initiatives.
- Considered an expert in building distributed systems and/or the infrastructure and tools to support it.
- Leadership & CollaborationProven ability to lead cross-functional teams and influence senior stakeholders without direct authority.Strong communicator who can translate complex technical strategies into impact-oriented outcomes.
- Proven ability to lead cross-functional teams and influence senior stakeholders without direct authority.
- Strong communicator who can translate complex technical strategies into impact-oriented outcomes.
- Execution FocusDemonstrated track record delivering products or features that generated measurable business value.Comfortable defining success criteria, metrics, and ROI for ambiguous, future-facing domains.
- Demonstrated track record delivering products or features that generated measurable business value.
- Comfortable defining success criteria, metrics, and ROI for ambiguous, future-facing domains.
- AI/ML & AutomationHands-on experience with AI or adjacent AI/ML platform experience with LLM integration and workflow automation, with demonstrated appetite to build toward agentic patternsDeep understanding of responsible AI practices and governance.
- Hands-on experience with AI or adjacent AI/ML platform experience with LLM integration and workflow automation, with demonstrated appetite to build toward agentic patterns
- Deep understanding of responsible AI practices and governance.
- Customer & Business MindsetPassion for solving real customer problems with elegant, scalable solutions.Ability to tie technical efforts directly to business KPIs (adoption, retention, revenue impact).
- Passion for solving real customer problems with elegant, scalable solutions.
- Ability to tie technical efforts directly to business KPIs (adoption, retention, revenue impact).
What Gives You an Edge:
- Experience working in cloud-native platforms or developer ecosystems.
- Prior leadership in scaling internal AI platforms or driving AI adoption across large organizations.
- Background in real-time data, event-driven architecture, or platform engineering.
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