GEN AI Engineer

Requirements:

• Bachelor's or Master's degree in computer science, software engineering, or a related technical discipline.
• Equivalent practical experience will be considered for exceptional candidates with a strong track record of delivery.
• 12+ years in software engineering, including 4+ years as a senior/principal architect designing distributed AI enterprise platforms.
• Visionary mindset with the ability to translate ideas into actionable strategies.
• Strong collaboration skills, partnering with segments' representatives, external technology vendors, and suppliers.
• Strong storytelling and communication skills.
• Strong problem-analysis, negotiating, and influencing skills.
• Learning agility and desire to learn new technology. Growth mindset for self and team, encouraging a culture of continuous learning and skill development.
• Strong hands-on expertise with Google Cloud Platform (Vertex AI, Cloud Run, IAM, Secret Manager) and/or Microsoft Azure (AI services, Container Apps, Entra ID, Key Vault); cross-cloud experience preferred.
• Practical experience integrating LLMs into production workflows, including prompt management, model abstraction, evaluation, and safety pipelines.
• Familiar with agentic AI patterns (ReAct, plan-and-execute, tool use, multi-agent delegation) and frameworks such as LangChain, LangGraph, and Semantic Kernel; the A2A/A2UI protocol is a plus.
• Advanced production-level Python skills for agent runtime, CLI, and skill development.
• DevOps proficiency: building GitHub Actions/DevOps pipelines, IaC (Terraform), container orchestration, and automated deployments.
• Skilled in identity/security standards (OAuth 2.0/OIDC, JWT, RBAC, Workload Identity Federation, managed identities).
• Experience with observability solutions: OpenTelemetry, distributed tracing, structured logging, dashboards (Cloud Monitoring, Azure Monitor).

Technical Landscape:

• Cloud Platforms: CP (Vertex AI, Cloud Run) and Azure DNA Environment (Azure AI Foundry, Container Apps).
• Identity: Microsoft Entra ID with Okta federation, a single identity plane for all personas.
• CI/CD: Azure DevOps, GitHub Actions.
• LLMs: Gemini (Pro, Ultra, Flash) via Vertex AI; GPT (4o, 4 5 series) via Azure OpenAI.
• Agent Interoperability: A2A protocol for agent-to-agent communication and task delegation.
• Observability: OpenTelemetry-based distributed tracing, structured logging, cost tracking.
• Governance: ARC, EA, DPIA, legal, and security gates enforced via CI/CD automation and compliance modules.
• Incident Management: ServiceNow integration across both platforms.

Skills

AI, Azure, GCP, GenAI, Generative AI, Google Cloud Platform, Microsoft Azure, architect, architecture