Staff Enterprise AI Engineer - Agentic Workflows & Productivity
New
Fully remote work flexibility across Canada and the U.S.Full-TimeStaff
Salary136,000 - 265,700 USD per year
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Job Details
- Experience
- 10+ years of software engineering experience, including 4+ years in a senior or staff technical leadership role.
- Required Skills
- PythonOAuthCI/CDLLM
Requirements
- 10+ years of software engineering experience, including 4+ years in a senior or staff technical leadership role.
- Strong hands-on coding ability with proficiency in Python and at least one additional modern programming language.
- Proven experience building and operating production AI/ML or LLM-based systems such as agents, RAG pipelines, or evaluation frameworks.
- Deep familiarity with Google Vertex AI, Gemini, and related cloud services including IAM, networking, observability, and cost optimization.
- Experience building developer platforms, internal tools, or AI-enabled productivity systems with adoption responsibility.
- Strong understanding of APIs, system integration, authentication, SSO, OAuth, and identity federation.
- Track record of leading cross-team technical initiatives and influencing without formal authority.
- Excellent communication skills with the ability to engage both technical and non-technical stakeholders effectively.
- Experience with agentic systems, orchestration frameworks, or tool/function calling is highly valued.
- Familiarity with enterprise AI governance, compliance, and secure deployment practices is a strong plus.
Responsibilities
- Lead the architecture, design, and rollout of enterprise AI platforms supporting agentic workflows across the organization.
- Build and maintain scalable, cost-efficient AI infrastructure, including model routing, cost controls, fallback models, and observability systems.
- Establish core platform foundations such as IAM, identity federation, tenant isolation, security guardrails, and compliance frameworks.
- Design and implement agent workflows across the product development lifecycle, including ideation, development, CI/CD, deployment, and monitoring stages.
- Develop self-service “agent factory” frameworks, enabling teams to safely build, deploy, and manage their own AI agents.
- Drive adoption of enterprise AI tools by providing training, enablement, and ongoing technical support.
- Build cross-platform interoperable agent systems with authentication, schema mapping, and integration across enterprise environments.
- Mentor engineers, lead technical reviews, and actively contribute to coding, debugging, and building reference implementations.
- Collaborate with product, engineering, and business stakeholders to translate needs into scalable AI-driven solutions.
- Oversee external delivery partners, ensuring alignment on scope, quality, and execution standards.
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