Senior AI Platform Engineer

Genesys

. Own end-to-end engineering and production reliability of Python services, APIs, automation, and integrations supporting AI platform administration, governance, security, privacy, and compliance .

Posted 10/14/2026full-timeMexicoSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced proficiency in Python for production services and automation, with a strong focus on designing and operating REST APIs and enterprise AI applications. Expertise in identity and access management, cloud infrastructure, and production reliability practices is essential.

Highest-signal resume keywords

Advanced Proficiency In PythonProduction Reliability Through SLOsDesigning And Operating REST APIsEnterprise Identity And Access ManagementCloud Infrastructure Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonREST APIsAsynchronous ProgrammingSQLInfrastructure As CodeAutomated TestingType CheckingException HandlingSecure Secrets ManagementData Modeling

Soft Skills

Clear Written CommunicationVerbal Communication

Tools & Technologies

AWSTerraformDatadogCloudWatchSplunkGrafanaPagerDutyOktaMicrosoft Entra IDOpenTelemetry

Certifications & Qualifications

SOC 2ISO 27001ISO/IEC 42001

Industry Keywords

AI GovernanceSaaSDevOpsEnterprise ScaleIdentity And Access Management

Tech Stack

Tools & technologies

AWSAzureCloudGrafanaPythonSplunkSQLTerraform

About the role

Key responsibilities & impact

Own end-to-end engineering and production reliability of Python services, APIs, automation, and integrations supporting 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, MCP, RAG, evaluations, guardrails, and human approval patterns
Evolve 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
Lead production reliability across enterprise AI tools using SLOs, monitoring, alerting, incident response, runbooks, and post-incident improvements
Plan platform upgrades, configuration changes, model and vendor API migrations, and production releases with 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
Design and automate identity and access controls using SSO, SAML, OIDC, SCIM, RBAC, least privilege, and audit logging
Implement safeguards for AI risks including prompt injection, sensitive-data disclosure, secrets leakage, insecure output handling, excessive agency, unsafe tool execution, and supply-chain risks
Translate governance requirements into enforceable controls and measurable evidence for SOC 2, ISO 27001, and ISO/IEC 42001
Evaluate AI platforms, MCP integrations, connectors, plugins, AI gateways, and emerging capabilities for architecture and investment decisions
Develop self-service provisioning, internal APIs, SDKs, infrastructure as code, and workflow integrations
Resolve complex Tier 2 and Tier 3 platform issues and maintain architecture documentation, technical runbooks, and operational playbooks
Partner with enablement teams and senior stakeholders to provide guidance, training, and platform improvements that increase safe AI adoption

Requirements

What you’ll need

5+ years of experience in platform engineering, IT operations, DevOps, or a related engineering discipline
At least 2 years supporting SaaS or AI tooling at enterprise scale
Advanced proficiency in Python for production services and automation, including REST services and clients, asynchronous programming, package management, type checking, automated testing, structured logging, exception handling, and secure secrets management
Experience designing, building, and operating REST APIs, webhooks, and event-driven workflows using OAuth 2.0 or OIDC, authorization controls, rate-limit handling, retries, idempotency, schema validation, and API version management
Hands-on experience delivering production AI applications or agentic workflows using enterprise model APIs or SDKs such as Anthropic, OpenAI, Amazon Bedrock, or Azure OpenAI
Experience with structured outputs, tool calling, retrieval, evaluations, and guardrails
Strong experience with enterprise identity and access management, including SSO, SAML, OIDC, SCIM provisioning, role-based access control, least privilege, and audit logging
Experience with platforms such as Okta or Microsoft Entra ID
Experience with cloud infrastructure, preferably AWS, containers, and infrastructure as code using Terraform, CloudFormation, or equivalent technologies
Proficiency in SQL and experience designing data models, pipelines, queries, and dashboards
Experience owning production reliability through SLOs, monitoring, alerting, on-call participation, incident management, and post-incident reviews
Experience with technologies such as Datadog, CloudWatch, Splunk, Grafana, PagerDuty, or OpenTelemetry
Strong software engineering practices using Git, pull requests, code review, automated testing, CI/CD pipelines, and secure development practices
Clear written and verbal communication skills
Ability to produce technical design documents, architecture documentation, runbooks, and stakeholder updates
Preferred: enterprise AI platform identity integrations, AI/ML platform concepts, MCP servers, AI gateways, LLM proxies, agent frameworks, vector databases, knowledge bases, embedding pipelines, RAG evaluation, enterprise architecture or systems integration, and relevant cloud, identity, or security certifications

Benefits

Comp & perks

Flexible-first culture with flexible ways of working
Mentorship, learning programs, leadership development and education support
Paid volunteer time
August Free Fridays
Well-being resources
Regionally tailored programs for employees and their families