G

Genesys

Cloud-based contact center software platform

AI Platform Engineer - Python, AWS

AI Application Engineering +1Updated on Nov 15
Full-timeTamil Nadu, IndiaNo salary listedRemote

About the Job

Requirements

  • At least 2 years of experience in software engineering, platform engineering, IT operations, or DevOps, with some exposure to SaaS or AI tooling administration.
  • Strong proficiency in Python for production application and automation development, including REST services and clients, data processing, package management, type checking, automated testing, structured logging, exception handling, and secure configuration management.
  • Hands-on experience designing and integrating REST APIs, webhooks, and event-based workflows, including authentication, authorization, rate-limit handling, retries, schema validation, and API-version management.
  • Hands-on experience building AI-enabled applications or workflows using one or more enterprise model APIs or SDKs.
  • Understanding of structured model outputs, function or tool calling, prompt and configuration versioning, human-in-the-loop controls, model evaluations, guardrails, and AI application observability.
  • Proficiency in SQL and experience designing data models, pipelines, queries, and dashboards for operational, security, compliance, cost, or usage reporting.
  • Experience with Git, pull requests, code review, automated testing, and CI/CD pipelines.
  • Working knowledge of identity and access management concepts, including provisioning, role-based access, and audit logging, for cloud-based platforms.
  • Familiarity with monitoring and alerting tools such as Datadog, PagerDuty, CloudWatch, or similar.
  • Experience with monitoring, alerting, and observability tools such as Datadog, CloudWatch, Splunk, Grafana, OpenTelemetry, or equivalent.
  • Clear written and verbal communication, and comfort following documented runbooks and escalating appropriately.

Responsibilities

  • Design, develop, test, deploy, and operate Python-based services and automation supporting AI governance, security, privacy, and compliance requirements.
  • Build tooling for AI application inventory, platform onboarding, risk classification, access reviews, policy compliance, control testing, exception management, approval workflows, and audit-evidence collection.
  • Translate governance policies and security requirements into enforceable technical controls, automated checks, alerts, and measurable control outcomes.
  • Develop security and compliance checks for sensitive-data exposure, inappropriate access, policy violations, secrets leakage, unsafe tool use, and other AI-specific risks.
  • Partner with Security, Privacy, Legal, Compliance, and Internal Audit to define evidence requirements and automate recurring evidence collection and reporting.
  • Build AI-enabled internal applications and workflows using enterprise model APIs and SDKs, structured outputs, function or tool calling, prompt and configuration versioning, and human-in-the-loop approval patterns.
  • Implement model and workflow evaluations, regression tests, guardrails, fallback behavior, rate limits, timeout handling, and cost controls.
  • Build dashboards for platform health, license utilization, token and cost consumption, access posture, policy exceptions, security events, control effectiveness, and audit readiness.
  • Enable successful platform onboarding for internal customers and operationally support their success.
  • Monitor uptime and health across enterprise AI tools, following established runbooks to detect and escalate degradations and assist with resolution alongside senior engineers.
  • Execute routine platform configuration changes and API version updates using documented change procedures while minimizing disruption to end users.
  • Maintain monitoring and alerting dashboards, flagging coverage gaps or false positives to senior engineers to keep runbooks accurate.
  • Administer day-to-day identity and access management tasks for the AI tool portfolio, including provisioning, de-provisioning, and role assignments, following corporate security policy.
  • Support periodic access reviews and compile evidence for compliance reporting and internal audits.
  • Partner with Security and Compliance teams on routine data-handling and governance checks, escalating exceptions to senior team members.
  • Build and maintain straightforward integrations between AI platforms and internal workflows, such as SSO connections and basic API connectors.
  • Serve as a point of contact for access, integration, and configuration issues, resolving routine cases and escalating complex ones.
  • Track usage and adoption metrics for assigned platform integrations, feeding accurate data into the team's reporting dashboards.

Desired Qualifications

  • Exposure to one or more enterprise AI platforms, such as ChatGPT Enterprise, Claude, Microsoft Copilot, Amazon Q, or Cursor.
  • Familiarity with SSO/SCIM concepts and identity providers such as Okta or Azure AD.
  • Experience integrating with platforms such as Okta or Microsoft Entra ID, ServiceNow, Splunk, Datadog, Snowflake, cloud security tools, GRC platforms, or DLP systems.
  • Familiarity with AI-specific security risks such as prompt injection, sensitive-data disclosure, insecure output handling, excessive agency, model abuse, unsafe tool execution, and supply-chain risks.
  • Familiarity with AI governance and information-security frameworks such as NIST AI RMF, ISO/IEC 42001, ISO 27001, SOC 2, and privacy-by-design principles.
  • Experience with LLM evaluation, AI red teaming, model or agent observability, prompt lifecycle management, or guardrail platforms.

About the Company

Genesys

Cloud-based contact center software platform

Genesys provides customer experience and contact center software. Its core product, Genesys Cloud CX, is a cloud-native platform for handling customer interactions across voice, messaging, email, chat, and social channels, with built-in AI for self-service, agent assistance, and journey orchestration. It also offers Genesys Cloud EX for workforce engagement and Multicloud CX and PureConnect for private cloud or on‑premises deployments, plus a marketplace called AppFoundry with hundreds of integrations. The company aims to help organizations deliver consistent, efficient customer experiences by routing interactions intelligently, automating self-service, and supporting agents across omnichannel channels at scale.

Company size
5,001-10,000
Company stage
Debt Financing
Total funding
$2.6B
Headquarters
Menlo Park, CA
Founded
2000

Recently Posted Jobs

Explore more opportunities at Genesys

See more jobs