Who you are

• You are a strategic engineering leader with deep systems thinking and a passion for building AI-native software at scale
• You empower your teams to own the full stack—balancing elegant APIs, intuitive UIs, and scalable orchestration pipelines
• You think like a product-minded CTO, guiding your engineers to deliver solutions that are both technically sound and business-aligned
• You thrive in complex, customer-facing environments, helping your teams navigate ambiguity, diagnose root problems, and architect intelligent workflows that scale
• You don’t just debug code—you coach engineers, debug systems, and align delivery with enterprise outcomes
• You lead with empathy, foster collaboration, and elevate the technical bar across every engagement
• Experience: In leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry
• Relevant Experience: 13+ years of software engineering, including 2+ years building systems in customer-facing or embedded roles
• System architecture: Proven ability to design and implement AI-native software in production-ready environments
• Engineering depth: Strength in backend (Python, Node.js, Java), frontend (React, Angular), APIs (REST/GraphQL)
• LLM tooling: Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management
• Performance & observability: Skilled in debugging distributed systems, tuning for latency, and implementing monitoring
• Platform mindset: Can contribute to shared SDKs and tools, raising engineering velocity for the whole org
• Product sensibility: Prioritize for user value, MVP iteration, and long-term scale
• DevOps fluency: Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code
• Field readiness: Able to travel up to 30% to embed onsite and deliver where it matters
• Experience integrating AI into SaaS platforms like ServiceNow or Salesforce
• Track record of production-ready deployments in secure, regulated enterprise environments
• Contributions to dev experience tooling, frameworks, or reusable AI scaffolds

What the job involves

• Our mission: We embed deeply with customers to build intelligent, scalable AI solutions for their most critical business challenges
• By solving complex real-world problems at speed, we codify repeatable patterns that scale across the enterprise—influencing both customer success and the future of the platform
• As a Director, Forward Deployed Software Engineer (FDSE), you lead high-performing engineering teams embedded with customers to deliver production-ready GenAI solutions
• You provide technical direction, unblock delivery challenges, and ensure architectural integrity across the full stack—from backend services and LLM pipelines to front-end integrations
• Your leadership turns prototypes into reference implementations, accelerates innovation, and drives repeatable success across industries
• You shape internal tooling, codify engineering patterns, and cultivate a culture of excellence and impact
• Lead Teams Building Solution-Ready Applications: Guide engineering teams in developing LLM-enabled applications that span backend logic, data orchestration, and front-end UI—ensuring technical excellence and business alignment
• Drive Field Execution: Oversee customer-embedded engagements, enabling your teams to adapt, deploy, and iterate solutions in live environments with agility and precision
• Codify Reusable Engineering Assets: Direct the creation of reusable libraries, prompt scaffolds, and modular components that accelerate future delivery and scale impact
• Shape Developer Experience: Channel field insights into platform and product teams, influencing roadmap priorities and improving tooling for broader engineering adoption
• Deliver End-to-End Solutions Through Teams: Ensure your teams deliver complete builds—from architecture to production-ready deployment—within agile sprint cycles
• Guide Versatile Engineering Practices: Mentor engineers across the stack—APIs, orchestration pipelines, vector databases, LLM frameworks, and UI components—fostering technical depth and adaptability
• Enable Agile Execution: Help teams navigate legacy integrations, ambiguity, and high-stakes environments while maintaining speed and safety in delivery
• Scale Through Codified Patterns: Lead the development of scaffolds, SDKs, and documentation that enable repeatable success across customer engagements
• Influence Platform Strategy: Translate field-tested insights into actionable feedback for product and platform teams, driving extensible improvements and innovation
• What Success Looks Like:
• Production-ready delivery: Your solution builds consistently convert to scaled deployments in production-ready environments
• Reusable impact: You author libraries, prompts, and scaffolds that power multiple deployments and projects
• Platform influence: Your work shapes internal tooling and is integrated into platform roadmap and primitives
• Velocity and precision: You move fast without breaking things—shaping resilient, secure systems in high-stakes contexts
• Engineering leadership: You are trusted by architects, PMs, and customer teams to lead implementation from zero to one

Benefits

• Commuter benefits
• Annual learning stipends
• Work from home opportunities
• Generous family leave
• Matched donations
• Flexible PTO
• 401(k) matching
• Paid volunteer time