This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Acceleration Engineer based in the United States.
This is a unique opportunity to shape the technical foundation of enterprise AI adoption at scale. As a senior individual contributor, you will define the architecture, standards, and infrastructure that enable secure, reliable, and reusable AI solutions across the organization. Working at the intersection of AI, data, platform engineering, and security, you'll collaborate with cross-functional teams to build scalable systems that empower innovation while maintaining strong governance. This highly influential role combines deep technical expertise with strategic thinking, offering the chance to establish engineering best practices and accelerate the development of next-generation AI capabilities in a fast-growing, remote-first environment.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Acceleration Engineer based in the United States.
This is a unique opportunity to shape the technical foundation of enterprise AI adoption at scale. As a senior individual contributor, you will define the architecture, standards, and infrastructure that enable secure, reliable, and reusable AI solutions across the organization. Working at the intersection of AI, data, platform engineering, and security, you'll collaborate with cross-functional teams to build scalable systems that empower innovation while maintaining strong governance. This highly influential role combines deep technical expertise with strategic thinking, offering the chance to establish engineering best practices and accelerate the development of next-generation AI capabilities in a fast-growing, remote-first environment.
Accountabilities:
- Define the architecture and technical strategy for an enterprise AI platform, establishing reusable frameworks, deployment standards, observability, and engineering best practices.
- Design secure AI connectivity patterns that enable large language models to access governed enterprise data through semantic layers, APIs, and scalable infrastructure.
- Develop governance-first AI infrastructure with authentication, authorization, auditability, privacy protection, and responsible AI deployment principles built into the platform.
- Create evaluation frameworks that measure AI quality, reliability, performance, and operational readiness before production deployment.
- Partner with Engineering, Data, Product, and Security teams to establish technical standards and accelerate AI adoption across the organization.
- Influence technical direction across multiple teams while improving platform scalability, developer experience, automation, monitoring, and operational excellence.
- Contribute to long-term architectural decisions that enable secure, maintainable, and high-performing AI systems.
- 8+ years of experience in software engineering, platform engineering, data engineering, machine learning infrastructure, or AI engineering.
- Proven experience architecting and delivering production-grade AI platforms, LLM-powered applications, autonomous agent systems, or similar intelligent solutions.
- Strong expertise designing systems that securely connect AI models with structured enterprise data through APIs, retrieval systems, semantic layers, or governance frameworks.
- Experience building distributed systems using modern cloud technologies, Kubernetes, Python, Snowflake, dbt, Airflow, Kafka, or comparable platforms.
- Strong understanding of AI infrastructure patterns, including function-calling frameworks, MCP servers, tool integrations, testing, monitoring, CI/CD, and observability.
- Demonstrated ability to define technical strategy and influence engineering organizations without direct management responsibility.
- Excellent collaboration, communication, and problem-solving skills with the ability to thrive in evolving technical environments.
- Experience with AI evaluation frameworks, semantic layer technologies, internal developer platforms, or regulated industries is considered a strong advantage.
- Competitive base salary ranging from $174,000 to $269,000, depending on experience and qualifications.
- Equity participation.
- Flexible, remote-first work environment with home office stipend.
- Flexible working hours and generous paid time off, including company holidays and seasonal breaks.
- Premium medical, dental, and vision insurance.
- Generous paid parental and caregiver leave.
- 401(k) retirement plan with company matching.
- Financial wellness resources and access to financial advisory services.
- Opportunities for continuous learning, technical growth, and collaboration with experienced engineering teams.
- Company-sponsored virtual and in-person team events throughout the year.