Sr. AI Platform Engineer

Be the one building AI-powered experiences where they matter most. At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships. Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day. Senior AI Platform Engineer Mexico Role Overview: The Senior AI Platform Engineer shapes the reliability, security, and scalability of the enterprise AI ecosystem that thousands of Genesys employees rely on to work more effectively. This role owns critical capabilities across platforms including Claude, ChatGPT Enterprise, Cursor, Amazon Q, and internal AI services, turning rapidly evolving AI technologies into dependable enterprise services with strong operational and governance foundations. You will operate at the intersection of AI platform engineering, automation, reliability, identity, and governance. You will influence strategy across Engineering, Security, Privacy, Legal, Compliance, Internal Audit, and business teams, translating enterprise requirements into scalable technical controls, integrations, and self-service capabilities. Your work will enable employees to use AI safely and effectively while improving platform availability, operational efficiency, cost visibility, and audit readiness. You will also help advance Genesys Cloud and the broader company AI strategy by building reusable engineering patterns that reflect empathy for users, strong collaboration across teams, and ambitious thinking about how AI can improve customer and employee experiences. The role provides exposure to enterprise AI architecture, agentic systems, platform governance, and organization-wide AI initiatives, with opportunities to expand technical leadership and influence platform direction as adoption and capabilities grow.

Own the end-to-end engineering and production reliability of Python services, APIs, automation, and integrations that support AI platform administration, governance, security, privacy, and compliance Design scalable AI-enabled applications and agentic workflows using enterprise model APIs and SDKs, structured outputs, tool calling, Model Context Protocol (MCP), retrieval-augmented generation (RAG), evaluations, guardrails, and human approval patterns Drive the evolution of AI governance tooling for application inventory, onboarding, risk classification, access reviews, policy compliance, control testing, exception management, approval workflows, and automated audit evidence Establish reusable engineering patterns for prompt and configuration versioning, regression testing, fallback behavior, rate limiting, timeout handling, observability, and cost controls that improve platform consistency and resilience Lead production reliability across enterprise AI tools, using SLOs, monitoring, alerting, incident response, runbooks, and post-incident improvements to maintain dependable service for thousands of internal users Plan platform upgrades, configuration changes, model and vendor API migrations, and production releases with clear testing, rollout, rollback, and stakeholder communication strategies Instrument AI applications and platforms to measure latency, errors, token consumption, output quality, adoption, license utilization, security events, policy exceptions, and cost, converting telemetry into platform and procurement decisions Design and automate identity and access controls using SSO, SAML, OIDC, SCIM, role-based access control, least privilege, and audit logging across the enterprise AI portfolio Implement technical safeguards for AI-specific risks including prompt injection, sensitive-data disclosure, secrets leakage, insecure output