AI Technical Architect
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Job Location:
Monthly Salary:
Posted on:
22 hours ago
Vacancies:
1 Vacancy
Job Summary
This manager-level position is responsible for people management and sales enablement. May also be responsible for project oversight of staff augmentation projects.
Required experience and qualifications
- 15 years of experience in infrastructure architecture cloud engineering or platform consulting with proven ownership of end-to-end architecture and delivery.
- Strong fundamentals in networking operating systems distributed systems and enterprise security.
- Proven experience delivering secure highly available platforms in regulated or enterprise environments.
- Deep hands-on experience with:
- Cloud infrastructure (OCI preferred; AWS/Azure/GCP acceptable)
- Enterprise network design (VPC/VCN VPNs routing firewalls proxies private endpoints DNS)
- Kubernetes/container platforms (OKE/EKS/AKS/GKE) secure cluster patterns and scaling strategies
- Infrastructure-as-Code (Terraform strongly preferred) and automation (Python/shell)
- Observability stacks (logs/metrics/traces) and integration with enterprise monitoring tools
- IAM vault/key management secrets handling encryption standards and audit controls
- Strong customer-facing skills: requirements discovery architecture documentation and delivery leadership.
Preferred (nice-to-have) skills
- LLM inference serving (open models and/or managed endpoints) multi-model routing and AI workload isolation.
- GPU platform engineering: scheduling node pool design performance tuning and cost controls.
- Experience implementing agentic AI runtime patterns with safe tool execution and enterprise guardrails.
- Hybrid and multi-cloud deployments including on-prem connectivity and enterprise integration patterns.
- Familiarity with data platforms relevant to AI (vector stores metadata stores object storage patterns).
Core competencies (what we value)
- Systems thinking and security-first architecture mindset
- Strong problem solving in constrained enterprise environments
- Crisp documentation and executive-ready communication
- Hands-on delivery orientation (not just advisory)
- Ownership urgency and accountability for production outcomes
Scope and impact (IC4/M3 expectations)
- Independently leads complex customer AI infrastructure programs from discovery through production and handover.
- Unblocks security/network constraints and drives approvals with clear evidence and mitigations.
- Establishes reusable referenceable blueprints (secure AI landing zones LLM hosting patterns DR templates observability baselines).
- Raises the quality bar by mentoring teams and institutionalizing guardrails reliability practices and delivery accelerators.
- Excellent leadership communication and stakeholder management skills.
- Manage a small team of AI consultants
Responsibilities
Ensures that operational policies are followed and that business objectives are achieved by focusing on best practices and process improvements. Responsible for operational metrics and business results for assigned area of responsibility. Typically manages individual contributors and/or entry-level managers. Monitors consultant activities and performance on projects (e.g. read status reports respond to staffing and availability issues pro-actively seek out project performance reviews etc.). May serve as project advisor for moderately complex engagements.
Qualifications
Career Level - M3
Required Experience:
Staff IC
Key Skills
- APIs
- SOAP
- Software Architecture
- .NET
- Design Patterns
- Enterprise Software
- AWS
- Solution Architecture
- Cloud Architecture
- Java
- SSO
- Oracle
About Company
As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when eve ... View more
