Company And Culture
Complex is the definitive platform for global youth culture and music lifestyle, seamlessly integrating cutting-edge content, commerce and live experiences with unparalleled scale. Through innovative content, Complex tells stories of music, streetwear and style, sports, art and beyond. Its content engages in a dynamic conversation with the audience, reflecting and shaping the zeitgeist of convergence culture. A powerful media juggernaut paired with a curated marketplace, Complex is redefining the way fans interact with their favorite brands and artists and reshaping the future of digital culture and commerce.
Why We're Hiring
Complex operates at the intersection of content, commerce, and culture—powering media, live experiences, marketplace, and audience engagement across sneakers, music, sports, and streetwear. This ecosystem generates a high volume of workflows, audience intelligence, and creative output. Much of that operational value, however, remains fragmented across SaaS platforms, manual processes, and institutional knowledge. We are building the next layer of infrastructure to change that.
The AI Orchestra Director: Agentic Infrastructure Engineer will embed directly within our technology organization, ensuring that every architectural decision drives measurable business outcomes. The role bridges system design, implementation, and operational impact. Complex is seeking an AI Orchestra Director—a hands-on technical architect and builder responsible for designing, deploying, and operationalizing our agentic AI infrastructure. This is not an advisory position. It is an execution-driven engineering mandate to build a parallel infrastructure layer that enables AI agents to:
- Automate core workflows
- Replace high-cost SaaS platforms with owned solutions
- Modernize data access and experimentation
- Generate proprietary, reusable intellectual property
- All while the business continues to operate without disruption
Work Schedule:
Possible freelance to hire, 4-6 month project Monday - Friday
What You'll Do
Top Three Strategic Priorities:1. Architect and Deploy the Agentic Infrastructure LayerDesign and implement a scalable runtime environment purpose-built for a media and commerce organization, including:Agent orchestration and task routingQuality gates and human-in-the-loop checkpointsLogging, observability, and convergence trackingCI/CD and deployment pipelinesOn-premise or hybrid environment architectureThis foundation must be secure, extensible, and maintainable by the existing engineering team
2. Lead the Tool Replacement ProgramAudit current SaaS licenses and identify high-cost, high-leverage replacement opportunities (e.g., CRM, analytics, workflow tools)Using agentic development practices:Build internal tools with AI agents writing and testing codeMaintain human review at critical checkpointsDeliver measurable license cost reductionsDemonstrate infrastructure ROI within the engagement periodThe objective: prove the system’s value by using agents to build the tools themselves
3. Codify Operational Workflows into a Reusable Skills LibraryPartner across departments to:Identify and document high-impact operational workflowsEncode them into version-controlled, reusable agent “skills”Transform tribal knowledge into durable company-owned IPThe result: a scalable library of automated capabilities that can operate independently of the engagement
Key Responsibilities:Architect and deploy the agentic infrastructure layer in collaboration with executive leadership and the Platform Studio engineering teamDesign a modern, growth-oriented data access layer built on existing Snowflake infrastructure and related data sourcesEnable agent-native querying, rapid experimentation, and insight generationEvaluate and integrate open-source orchestration tools to maintain vendor-agnostic flexibilityImplement test-driven development enforcement, intelligent retry logic, and convergence trackingEstablish governance frameworks with human-in-the-loop checkpoints for production deployment and auditabilityEmbed seamlessly with existing engineering teams—building trust, not parallel power structuresDevelop documentation, training protocols, and knowledge-transfer systems to ensure long-term sustainabilityPartner with the COO and department leaders to prioritize automation initiatives that simultaneously reduce cost and increase velocityFoster a culture shift toward agentic development as a core capability within the organization
Who You Are
Proven experience building and deploying AI agent infrastructure in production environmentsDeep proficiency across LLM orchestration frameworks, retrieval-augmented generation (RAG), prompt engineering, and agentic coding workflowsStrong systems architecture background with infrastructure designed for long-term maintainabilityExperience with data engineering and analytics infrastructure (Snowflake and API-based systems preferred)Comfort evaluating and integrating open-source tooling within a multi-model ecosystem (e.g., Claude, Codex, Gemini, open-source models)Git-native workflow mindset (branches, PRs, CI/CD, TDD)Exceptional ability to translate complex architecture into business-aligned outcomesExperience embedding within existing teams and leaving them stronger than you found themMedia, entertainment, or commerce industry experience preferred but not requiredComfortable with whiteboarding systems with executive leadershipCreating shipping production-ready pipelinesReviewing agent-generated codeAbility to train teams to extend what you’ve built
Success Metrics (By the end of the 12 week engagement, you will have delivered):A working agent runtime environment with orchestration, logging, quality gates, and CI/CD pipelinesAt least two deployed internal SaaS replacements with documented cost savingsA versioned skills library containing a minimum of ten codified operational workflowsA defined and partially implemented data access layer serving both human users and AI agentsComplete knowledge transfer to the existing engineering teamSeamless organizational integration with no structural friction
What Success Looks Like:Success is not measured solely by architectural elegance – It is measured by operational independenceWorkflows that execute autonomouslyTools built internally rather than rentedData systems that surface insights proactivelyAn engineering organization fluent in agentic development
