AI Platform Lead

AI Platform Lead Our client is a global LegalTech organization delivering data-driven digital solutions that help businesses manage regulatory complexity, improve compliance processes, and make smarter decisions. I want to apply! We usually respond within a day 📁 About our client: Our client is the global leader in regulatory and sustainability intelligence, helping the world's largest companies navigate Environment, Health & Safety, Corporate Sustainability, and Product Compliance. They are reinforcing their AI capabilities to keep their leadership as an AI-native compliance intelligence platform, with a foundational AI platform built around ontology, data, and platform surfaces, strong CAIO sponsorship, and direct executive air cover for the product layer of the AI transformation. 🚀 Responsibilities: Platform Ownership Design, build, and own the AI platform end-to-end: LLM gateway, prompt registry, runtime guardrails, agent framework, evals pipeline, and the deployment substrate underneath. Champion platform standards: repo structure, testing, deployment safety, rollback patterns, and cost controls. CI/CD & Infrastructure Architect and operate CI/CD for AI services: containerized deployment, infrastructure-as-code (Terraform or Bicep), Kubernetes / AKS, pipeline tooling, and secrets management. Prototype new platform capabilities rapidly with AI coding assistants, validating patterns against real workloads before productizing them. Agentic Interfaces & MCP Build and operate the MCP server layer and agentic interfaces that expose product capability to external agents, Copilot, Teams, and partner surfaces. Carry strong opinions on how agents, tools, and MCP servers actually get deployed and operated in production. Observability & MLOps Own observability for AI workloads: latency, cost, token usage, guardrail hits, eval drift, agent trace capture. Splunk and equivalents are daily tools. Integrate with ML experiment tracking (MLflow) and ensure models, prompts, and agent configurations flow cleanly from dev to production. Team & Technical Leadership Lead a small squad of platform and AI DevOps engineers as a player-coach: roughly half of your time on hands-on build, half on direction-setting, review, and growing the people around you. Own hiring into the team and set the technical and operational bar: code review culture, infra patterns, and the discipline that keeps AI services healthy at 3am. 👤 Profile sought: Experience: Clear history of shipping and operating AI or platform infrastructure that real users depend on, with specific systems and outcomes you can point to. Hands-on experience with agent frameworks and LLM orchestration. Direct experience building or operating MCP servers, or comparable tool-use / function-calling surfaces, is highly preferred. Track record designing LLM gateways, prompt registries, or runtime guardrails, or operating the equivalent primitives. Technical skills: Strong production experience with cloud platforms (Azure preferred, AWS or GCP a plus). Deep comfort with Terraform or Bicep, Kubernetes / AKS, and the full lifecycle of infrastructure-as-code. Real CI/CD ownership (Bitbucket Pipelines, GitHub Actions, Azure DevOps, or equivalents): repo structure, test execution, and safe paths to production. Strong Python skills plus meaningful experience in at least one compiled or systems-level language (C# / .NET, C++, Go, Rust, or similar). Observability for AI (Splunk, OpenTelemetry, or similar) as second nature. Daily-driver Linux comfort: shell scripting, process management, troubleshooting, system configuration. Active user of AI coding assistants, integrated into daily workflow, with a clear point of view on what they are good and bad at. Bonus: Experience with MLflow, experiment tracking, or ML pipeline tooling at scale. Deep familiarity with Azure Kubernetes Service (AKS) and the Azure ecosystem specifically. Background in multi-provider LLM routing, cost optimization, or caching strategies. Experience with EU AI Act runtime controls or comparable regulated-AI compliance tooling. Contributions to open-source agent frameworks, MCP servers, or LLM tooling. Experience in regulated industries (EHS, legal, financial, healthcare). Languages: Fluent English required. Soft skills: Player-coach leadership style: technically credible, willing to ship gateway, pipeline, and agent runtime code yourself, equally focused on growing the team. Opinionated about tools, pragmatic about deadlines. Strong communicator across technical and product audiences. Bias for delivery, operational discipline, and on-call ownership over research polish. 🌍 Benefits & Culture: Tech stack: Azure / AKS, Terraform or Bicep, Kubernetes, Python, LLM gateways, MCP, agent frameworks, MLflow, Splunk, OpenTelemetry. Direct ownership of the platform every AI product at the company runs on. Direct access to leadership and the Chief AI Officer: short feedback loops, real influence on architecture and direction. A seat on a small, high-impact AI team building products that matter at global scale. Culture that treats AI tools as force multipliers, not novelties. Competitive compensation, benefits, and flexibility. Hybrid in Lisbon's Office role (3 days a week at the office) 💼 Department: AI & Engineering 📍 Location: Lisbon 📆 Start date: ASAP Locations Lisboa Remote status Hybrid