Lead AI Engineer

About the Role:

Most companies are still figuring out what it means to be AI-native. Ovative is building it. We have 500+ people across media, measurement, analytics, and strategy who are being asked to work fundamentally differently — and this role is responsible for building the technical infrastructure that makes that possible at scale. Not a pilot. Not a proof of concept. A production system that changes how an entire organization operates. 

This role is the technical owner of that system. You will design and build the integration layer that connects our AI platform to the tools and data sources people work in every day, architect the orchestration logic that enables automated multi-step workflows, and establish the technical standards and security framework that govern how AI operates across the organization. 

The primary measure of success in this role is not architectural elegance — it is whether the practitioners, analysts, and domain experts who are not engineers can build and run workflows without needing engineering involvement at every step. The infrastructure you build disappears into the work of non-technical people. That is the job. 

This is not a purely architectural role. You will build. You will also serve as the technical escalation point for complex builds that go beyond what practitioners and domain experts can execute independently. You will report directly into the AI Lead. 

Responsibilities of the Lead AI Engineer: 

• Develop reusable infrastructure patterns and guardrails that allow domain experts and practitioners to build their own workflows without requiring engineering involvement at every step 

• Design the abstraction layer that separates technical implementation from business logic, so non-engineers can configure and iterate without breaking the underlying system 

• Serve as the technical owner of Ovative's AI workflow infrastructure, leading the system from initial design through production use 

• Design and build the integration layer connecting our enterprise AI platform to the tools and data sources the organization depends on — project management, communications, analytics, and others 

• Architect the orchestration logic that enables multi-step automated workflows, including how inputs are routed, how outputs connect back into existing systems, and where human review is required 

• Own the system write-back layer: design and maintain the bidirectional integration that reads from and writes results back to task management and operational systems, including handling output routing, status updates, and the human action loop 

• Own the security and governance framework for all AI integrations and automated workflows: access controls, credential management, audit logging, and principle of least privilege applied from the start, not retrofitted 

• Establish and enforce technical standards for how integrations are built, permissioned, and monitored; partner with IT and security to ensure compliance with SOC2 and evolving data governance requirements 

• Build and maintain CI/CD pipelines and infrastructure-as-code practices for the AI platform layer so that deployments are repeatable, auditable, and low-risk 

• Serve as the technical reviewer for new agents and automated workflows before organization-wide deployment, and own the standards those workflows must meet 

• Design and maintain a post-deployment monitoring framework for agents and automated workflows — not just pre-deployment review, but ongoing observability into how workflows behave in production, where failures occur, and when intervention is needed 

• Partner with the AI Lead and stakeholders to evaluate incoming requirements against technical feasibility — surfacing constraints, tradeoffs, and alternatives so the right solution gets built; translate approved requirements into clear technical specifications that guide implementation 

• Document architecture decisions and system behavior so the infrastructure is legible and maintainable beyond any one person 

Requirements:

• 8+ years of experience in software engineering, platform engineering, or applied technical roles 

• Demonstrated experience designing and delivering AI-powered workflow systems, integration platforms, or agent-based automation in production environments 

• Strong proficiency in Python and SQL, with experience building production platform or data services 

• Experience designing and building API integrations, connector frameworks, or workflow automation systems at enterprise scale — including bidirectional write-back to operational systems 

• Hands-on experience with cloud platforms (AWS, GCP, or Azure); experience with Databricks is strongly preferred 

• Hands-on experience with MCP (Model Context Protocol) or equivalent agent orchestration frameworks; this is a core part of what you will build and operate 

• Demonstrated hands-on experience working with large language models in production: context windows, prompt structure, tool use, and agent behavior 

• Hands-on experience operationalizing security requirements: access control, credential management, audit logging, and principle of least privilege in systems with broad organizational reach 

• Strong communication skills and demonstrated ability to lead technical discussions across disciplines; you can explain architecture decisions to a business leader as clearly as to an engineer 

• Experience partnering with non-technical stakeholders to define system capabilities, including communicating feasibility, constraints, and tradeoffs 

• Demonstrated success building platforms or infrastructure that non-engineers actually use — not just internal developer tooling 

Preferred 

• Experience working with Claude Enterprise or the Anthropic API 

• Experience operating AI systems in governed or compliance-sensitive environments 

• Experience building multi-step or multi-agent automated workflows in a production environment 

• Exposure to project management, analytics, or communications platform integrations 

• Prior experience in a marketing analytics, media, or professional services environment