AI Platform Engineer, Python, AWS

🔥 48 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟢 Junior

🟡 Mid-level

🔙 Backend Engineer

🚫👨‍🎓 No degree required

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Genesys

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1990

💼 Consulting

🏥 Healthcare

🛡️ Insurance

Consulting • Healthcare • Insurance

Genesys is a leading provider of AI-powered experience orchestration solutions designed to deliver personalized experiences at scale. Their offerings include comprehensive contact center software, workforce engagement management solutions, and an open platform with cloud architecture. Genesys Cloud CX and EX platforms optimize both customer and employee experiences using intelligent automation and embedded AI, allowing seamless engagement across any channel. With a focus on various industries including banking, healthcare, retail, insurance, and government, Genesys assists organizations in transforming customer and employee interaction landscapes. Additionally, their AppFoundry Marketplace offers pre-integrated applications to extend platform functionalities.

📋 Description

• Design, develop, test, deploy, and operate Python-based services and automation supporting AI governance, security, privacy, and compliance • 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 • 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 platform onboarding for internal customers and operationally support their success • Monitor uptime and health across enterprise AI tools, following runbooks to detect and escalate degradations • Execute routine platform configuration changes and API version updates using documented change procedures • Maintain monitoring and alerting dashboards • Administer identity and access management tasks, including provisioning, de-provisioning, and role assignments • Support periodic access reviews and compile compliance evidence • Build and maintain integrations between AI platforms and internal workflows • Resolve routine access, integration, and configuration issues and escalate complex cases • Track usage and adoption metrics for assigned platform integrations

🎯 Requirements

• 2+ years of experience in software engineering, platform engineering, IT operations, or DevOps, with some exposure to SaaS/AI tooling administration • Strong proficiency in Python for production application and automation development • Hands-on experience designing and integrating REST APIs, webhooks, and event-based workflows • Hands-on experience building AI-enabled applications or workflows using enterprise model APIs or SDKs • Understanding of structured model outputs, function or tool calling, prompt/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 • Experience with Git, pull requests, code review, automated testing, and CI/CD pipelines • Working knowledge of identity and access management concepts for cloud-based platforms • Familiarity with monitoring and alerting tools • Experience with monitoring, alerting, and observability tools • Clear written and verbal communication, and comfort following documented runbooks and escalating appropriately • Preferred: exposure to enterprise AI platforms, SSO/SCIM and identity providers, integrations with enterprise platforms, AI-specific security risks, AI governance and information-security frameworks, LLM evaluation, AI red teaming, model or agent observability, prompt lifecycle management, or guardrail platforms

🏖️ Benefits

• Flexible ways of working • Mentorship • Learning programs • Leadership development • Education support • Paid volunteer time • August Free Fridays • Well-being resources • Regionally tailored programs for employees and their families