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FirstCry

Posted 27 Aug 2026

GEN AI Engineer

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Employment
Full time
Team
Data Science & Analytics
Posted
27 Aug 2026

About the role

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.

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