Staff AI Platform Engineer

Genesys•Virginia City, MT

1d•$147,100 - $258,700•Remote

About The Position

AI capabilities at Genesys power how thousands of employees deliver better customer and employee experiences every day. This role owns the evolution of the enterprise AI platform ecosystem, ensuring it is scalable, secure, and built for meaningful business impact. You will shape how AI tools are architected, integrated, and governed, directly influencing how innovation is delivered across the company. At Genesys, we are advancing experience orchestration through AI and empathy, and this role sits at the center of that transformation. Operating with high autonomy, you will partner with engineering, security, legal, and business leaders to turn AI capability into reliable, well-governed infrastructure. Your work directly informs platform investment decisions, enterprise adoption strategies, and long-term architecture direction. This is a high-influence technical role for someone who leads through expertise and credibility, with visibility across enterprise initiatives and the opportunity to shape platform engineering standards at scale.

Requirements

8+ years of experience in platform engineering, DevOps, or IT operations within enterprise environments
At least 4 years of experience building or administering enterprise SaaS platforms at scale with 1-2 years working with enterprise AI platforms.
Demonstrated ability to influence architecture and roadmap decisions through hands-on technical design, evaluation, and advisory work
Strong experience building internal platforms, including self-service tooling, APIs, SDKs, and infrastructure-as-code solutions
Deep expertise in identity and access management, audit logging, and governance frameworks for cloud-based systems
Proven track record of mentoring engineers and influencing technical standards across teams or organizations
Strong scripting and automation experience using Python, Bash, or similar languages
Experience with monitoring and alerting platforms such as Datadog, PagerDuty, or CloudWatch
Experience administering enterprise AI platforms such as ChatGPT Enterprise, Claude, or Cursor

Nice To Haves

Experience integrating enterprise systems with identity providers such as Okta or Azure AD using SSO and SCIM
Familiarity with AI platform concepts including API rate limiting, token-based billing, prompt management, and model versioning
Familiarity with machine learning and MLOps concepts, including model lifecycle management, data pipelines, and production deployment patterns
Experience supporting AI ecosystems beyond GenAI, including knowledge base, context management, or memory systems that enable scalable and reliable AI applications
Background in enterprise architecture or large-scale systems integration within a technology organization

Responsibilities

Own the end-to-end architecture and evolution of the enterprise AI platform ecosystem, ensuring scalability, security, and performance across tools and integrations
Drive platform strategy decisions through build versus buy analysis, cost modeling, and risk evaluation that guide leadership investment and consolidation priorities
Design and implement self-service platform capabilities that reduce onboarding time and accelerate enterprise-wide adoption of AI tools
Build and standardize internal APIs, SDKs, and infrastructure-as-code solutions that enable consistent, reusable, and scalable integrations
Lead the transition from manual administration to automated, API-driven platform operations to improve efficiency and reduce operational friction
Establish and scale identity and access management, audit logging, and governance frameworks that strengthen security posture and compliance readiness
Translate platform usage, cost, and adoption telemetry into clear, actionable insights that inform procurement, roadmap planning, and enterprise strategy
Lead incident response strategy and implement monitoring and alerting systems that improve reliability and reduce platform disruption