AI Architect

AI Architect

Location:

LA, California (Onsite)

Duration:
Full-time

Job Description:

Must Have

Skills:

• Strong experience in enterprise solution architecture, backend engineering, and distributed systems design.
• Expertise in Python, Type Script, Node.js, Java, Go, or similar backend technologies.
• Strong experience designing APIs, integration platforms, event-driven architectures, and workflow orchestration systems.
• Hands-on experience with GenAI applications, AI agents, RAG workflows, tool-calling systems, and enterprise chatbot platforms.
• Strong understanding of LLM ecosystems including OpenAI, Claude, ChatGPT Enterprise, Azure OpenAI, Amazon Bedrock, Google Vertex AI, Databricks, or similar AI platforms.
• Experience designing orchestration frameworks, agent runtimes, workflow engines, and stateful task execution systems.
• Strong understanding of prompt engineering, structured outputs, guardrails, function calling, and AI safety controls.
• Experience integrating enterprise collaboration and workflow platforms including Slack, Jira, Zendesk, Service Now, and Confluence.
• Strong understanding of enterprise identity and access management including Okta, SCIM, SSO, RBAC, ABAC, secrets management, and governance controls.
• Experience with observability platforms such as Open Telemetry, monitoring frameworks, logging, tracing, metrics, and operational dashboards.
• Strong knowledge of secure architecture practices, enterprise governance, data privacy, compliance, and operational reliability.
• Experience with CI/CD pipelines, Dev Ops practices, deployment automation, rollback strategies, and operational lifecycle management.
• Strong stakeholder management and leadership skills across architecture, engineering, AI Ops, governance, security, and business teams.

Key Responsibilities:

• Design and architect enterprise-grade AI and backend solutions supporting scalable, reliable, and secure distributed systems.
• Lead the development of APIs, integration platforms, and event-driven architectures to support enterprise workflows and automation.
• Drive the design and implementation of GenAI-powered applications, AI agents, and RAG-based systems for enterprise use cases.
• Define and implement LLM orchestration frameworks, agent runtimes, and workflow engines to support complex AI-driven operations.
• Establish best practices for prompt engineering, guardrails, structured outputs, and AI safety controls across applications.
• Integrate enterprise platforms such as Slack, Jira, Zendesk, Service Now, and Confluence with backend systems and AI services.
• Design and enforce identity and access management solutions using Okta, SCIM, SSO, RBAC, ABAC, and secrets management.
• Implement observability solutions including logging, monitoring, tracing, and metrics for AI and backend platforms.
• Ensure adherence to security, governance, compliance, and data privacy standards across all systems and integrations.
• Build and maintain CI/CD pipelines and Dev Ops processes for efficient deployment, automation, and lifecycle management.
• Collaborate with cross-functional stakeholders across architecture, engineering, AI Ops, governance, and business teams to align solutions with organizational goals.
• Provide technical leadership, mentorship, and guidance to engineering teams in building scalable AI and backend systems.