AI PLATFORM ENGINEER

Position Overview:

This senior engineer turns the client's responsible agentic factory strategy into repeatable infrastructure, automated delivery pipelines, production-grade operating practices, and clear engineering standards. The role blends hands-on AI platform delivery with governance, observability, secure deployment, and mentoring across technical teams.

Mission: Architect, standardize, automate, and operate secure responsible agentic AI platform deployments across cloud, datacenter, development, UAT, and production environments.

Key Responsibilities:

• Define standards-based deployment patterns for responsible AI agents, reusable platform capabilities, and secure agent runtime architectures, including identity, access, and secrets management.
• Automate AI platform buildout, release standardization, environment provisioning, CI/CD, Terraform/Helm deployments, and operational runbooks.
• Operate reliable AI platform services with incident response, capacity planning, OpenTelemetry traces/logs/metrics, monitoring, rollback, and disaster recovery practices.
• Collaborate across InfoSec, CloudOps, DevOps, and platform engineering teams to create responsible agentic factory standards for guardrails, governance, secure releases, observability, and production readiness.
• Coach engineers, lead design reviews, guide implementation toward approved architecture patterns, and drive practical tradeoffs across cost, speed, reliability, and security.

Required Qualifications:

• 5 years of engineering experience, including 3+ years building and operating production systems on cloud platforms.
• Strong experience with GCP/AWS or hybrid cloud/datacenter deployments; Docker, Kubernetes, GitHub Actions with reusable workflows and self-hosted runners, Terraform, and Helm.
• Working knowledge of authentication and authorization (OAuth 2.0, OIDC, SAML, JWT, RBAC, IAM), including workload identity, service-to-service auth, and securing API and tool access.
• 3+ years scripting and automation experience, preferably Python and JavaScript, with strong troubleshooting across Linux, containers, Kubernetes, networking, and production incidents.
• Ability to architect secure, cost-efficient hosting for open-source LLMs, on-prem or in dedicated cloud, as an alternative to commercial model APIs.

Nice to have:

• 2+ years using AI coding tools (Claude Code, Codex, Cursor) to automate platform buildout, deployment, testing, troubleshooting, and documentation.
• Agentic AI frameworks (LangGraph, Google ADK), agent-to-agent (A2A) patterns, tool calling, AI workflow orchestration, RAG, evaluation, and responsible AI guardrail design.
• AI-specific observability and tracing (LangSmith, Grafana/LGTM), GPU infrastructure for model serving (NVIDIA GPU Operator, Vertex AI), and DAG-based orchestration (Dagster, Prefect, Airflow).
• Excellent communication, mentoring, stakeholder management, and project planning, with flexibility for critical deployments and production incidents.

Benefits/Info extra:

• Full remote working;
• Budget: $35/h - $40/h
• Collaboration contract (SRL) only;
• Average of 150 hours per month;
• Flexible working hours.

Only shortlisted candidates will be contacted for the next stage of the recruitment process.