Serve as the primary AI engineering partner to the CEO and executive leadership team, translating ideas, strategic questions, and emerging concepts into production-ready AI agents and workflows with minimal oversight.
Independently take ideas from concept to production, shaping problem statements, designing system architecture, implementing code, validating outputs, and operationalizing solutions without requiring heavy product or engineering management.
Design and implement complex, multi-step agentic workflows, including multi-agent orchestration, retrieval-augmented generation (RAG), tool use, memory strategies, evaluation frameworks, and cross-system automation.
Develop production-grade AI systems using modern LLMs, orchestration frameworks, and internal tooling, with strong attention to scalability, performance, observability, and clean engineering practices.
Operationalize AI responsibly by implementing guardrails, structured evaluations, monitoring, and validation layers to ensure predictable behavior, reliability, and compliance.
Partner closely with Security and Legal to properly gate sensitive use cases, implementing access controls, audit logging, data minimization, and enterprise-grade governance patterns while balancing safety and speed.
Translate ambiguous, high-visibility problems into clear technical solutions, balancing speed, quality, and risk while maintaining a high bar for accuracy and trust.
Evaluate, select, and rationalize AI tools and platforms, contributing to capability-to-tool decisions and ensuring consolidation, security alignment, and long-term sustainability across the enterprise.
Support post-launch adoption and iteration, incorporating feedback, refining workflows, and continuously improving performance, usability, and measurable impact.
Contribute to org-wide AI maturity by documenting architectural patterns, sharing best practices, and establishing repeatable approaches that elevate internal AI capabilities across Webflow.

Requirements

7-10+ years of professional software engineering experience designing, building, and operating complex production systems in cloud environments (or equivalent practical experience).
Proven experience building and deploying AI-powered systems in production, including agent-based or multi-step workflows (RAG, orchestration, tool-calling, memory strategies, evaluation, and failure handling).
Strong proficiency in modern programming languages (e.g., Python, TypeScript) with demonstrated ability to write clean, maintainable, production-quality code.
Deep engineering discipline across clean architecture, distributed systems, APIs, CI/CD, testing strategies, and production observability.
Experience partnering directly with senior or executive stakeholders, translating ambiguous ideas into scalable, technically sound solutions with measurable impact across enterprise systems.

Benefits

Ownership in what you help build.
Health coverage that actually covers you.
Support for every stage of family life.
Time off that’s actually off.
Wellness for the whole you.
Invest in your future.
Monthly stipends that flex with your life.
Bonus for building together.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI systems developmentmulti-agent orchestrationretrieval-augmented generationsystem architecture designproduction-grade codecloud environmentsPythonTypeScriptclean architecturedistributed systems

Soft Skills

problem-solvingcommunicationcollaborationstakeholder managementadaptabilityattention to detailcritical thinkingorganizational skillsleadershipfeedback incorporation