AI PLatfrom Engineer

Saxon Global • Richardson, TX

11d

About The Position

The Senior Engineer drives implementation of the organization's responsible AI and agentic systems strategy through scalable infrastructure, automated delivery pipelines, production-grade operational practices, and engineering standards. The position combines hands-on AI platform engineering with governance, observability, secure deployment, and technical leadership across engineering teams.

The engineer establishes reusable deployment patterns and platform capabilities for AI agents, automates provisioning and release processes, and operates reliable AI platform services. The role collaborates with security, cloud infrastructure, DevOps, and platform engineering teams on governance, guardrails, secure releases, observability, and production readiness. It also provides technical leadership through mentoring, design reviews, and guidance toward architectural standards, while balancing cost, delivery speed, reliability, scalability, and security.

Success means deployment patterns are documented, standardized, automated, observable, and auditable across AI and agent-based workloads; delivery processes become more efficient, secure, consistent, and governable; and security, compliance, governance, observability, and responsible automation are embedded throughout the software delivery lifecycle.

Requirements

• 8–10 years of software engineering experience, including at least 7 years building and operating production systems in cloud environments and hands-on experience deploying AI/ML services into production.
• 2–3 years of experience utilizing AI-assisted development tools, such as Claude Code, Codex, Cursor, GitHub Copilot, or similar, to accelerate platform development, deployment, testing, troubleshooting, and documentation.
• Strong experience with AWS, GCP, Azure, hybrid cloud, or on-premises infrastructure; Docker; Kubernetes; GitHub Actions or equivalent CI/CD tooling; Terraform; and Helm.
• Working knowledge of authentication and authorization technologies, including OAuth 2.0, OpenID Connect (OIDC), SAML, JWT, Role-Based Access Control (RBAC), and Identity and Access Management (IAM).
• Experience implementing workload identity, service-to-service authentication, and secure API and tool access.
• 4+ years of scripting and automation experience, preferably with Python and JavaScript, including troubleshooting across Linux, containers, Kubernetes, networking, and distributed production systems.
• Ability to architect secure and cost-efficient hosting solutions for open-source large language models (LLMs) in cloud, private cloud, or on-premises environments.

Nice To Haves

• Experience with agentic AI frameworks such as LangGraph or Google ADK, agent-to-agent communication patterns, tool integration, workflow orchestration, Retrieval-Augmented Generation (RAG), AI evaluation frameworks, and guardrail design.
• Familiarity with AI observability and tracing platforms such as LangSmith or Grafana/LGTM, GPU infrastructure for model serving, and orchestration platforms such as Dagster, Prefect, or Apache Airflow.
• Strong communication, mentoring, stakeholder management, and project planning skills.
• Ability to support critical production deployments and incident response activities when necessary.

Responsibilities

• Define standards-based deployment patterns for AI agents, reusable platform capabilities, and secure runtime architectures, including identity, access, and secrets management.
• Automate AI platform provisioning, standardized release processes, environment management, CI/CD pipelines, infrastructure-as-code deployments, and operational documentation.
• Operate and maintain reliable AI platform services through incident response, capacity planning, monitoring, observability, rollback procedures, and disaster recovery capabilities.
• Collaborate with security, cloud infrastructure, DevOps, and platform engineering teams to establish governance, guardrails, secure release practices, observability standards, and production readiness requirements.
• Mentor engineers, lead technical design reviews, guide implementations toward established architectural standards, and balance tradeoffs among cost, velocity, reliability, scalability, and security.
• Support critical production deployments and incident response activities when necessary.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed