📁 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