Senior MLE Staff Engineer

About The Role 💻

We are looking for a Senior MLE Staff Engineer who is an expert in the deployment and scaling of LLMs and Agentic systems. In this role, you will bridge the gap between machine learning experimentation and production at scale by building the robust, highly efficient platform that powers our AI initiatives.

While our Data Science teams focus on developing and tuning state-of-the-art models, you will be the owner of the platform that enables them. You will define best practices, build automated pipelines, and ensure that our infrastructure can handle complex agentic workflows with high reliability and performance. This is a role for a visionary who stays ahead of the daily shifts in the AI landscape and can rapidly adapt our stack to leverage emerging trends.

For more insight into the technologies used by the engineering team at Clarity AI, please explore our Tech Stack

What You’ll Be Doing 🚀

As a Senior MLE Staff Engineer, you will be responsible for:

• GenAI Platform Engineering: Designing and developing the core platform that enables the efficient deployment, scaling, and management of LLMs and multi-agent systems.
• Infrastructure for Agents: Building specialized infrastructure to support long-running agentic workflows, including state management, tool-calling interfaces, and complex reasoning loops.
• High-Scale Productionization & Model Serving: Scaling inference for LLMs to handle global demand while optimizing for latency, throughput, and cost. Implement standard batch and online serving with controlled rollback.
• Build & Delivery: Establishing the "Golden Path" for model deployment through a self-service path to move code, data, and models to production safely and reproducibly, including automated evaluation frameworks, safety guardrails, and CI/CD/CT pipelines.
• Strategic Vision & Product Management: Continuously monitoring the AI ecosystem and proactively evolving our platform to maintain a competitive edge. This includes adopting best practices in Platform Product Management and driving the adoption of golden-path solutions.
• End-to-End Observability: Implementing deep observability for LLMs, tracking not just system health but providing unified visibility into health, impact, and root cause across data, ML, and GenAI (including model hallucinations, token usage, and RAG performance).
• Collaborative Foundation: Providing the tools and abstractions that allow Data Scientists and stakeholders to move from a "tuned model" to a "production service" with zero friction.

Location 🌍

The role is based in our tech hub in Madrid, Spain, but we are remote-friendly and open to the CET timezone +/- 2 hours.
Way of Working: Remote/Hybrid

What You’ll Need 👀

• LLM & Agent Expertise: Deep, hands-on experience deploying Large Language Models and complex agentic architectures at scale.
• GenAI Platform Specifics: Proven experience in implementing Prompt Lifecycle Management (versioning, testing, and deploying prompts as code), an LLM Abstraction Layer (provider-agnostic access), and systems for Cost & Usage Control (visibility and limits on GenAI spend per use case).
• Evaluation & Benchmarking Mastery: Expert-level experience building automated evaluation pipelines and frameworks (e.g., Ragas, DeepEval, G-Eval) and implementing LLM-as-a-judge patterns to validate model quality, grounding, and safety in CI/CD.
• Platform & MLOps Mindset: A proven track record of building platforms or shared infrastructure. Deep understanding of MLOps concepts like Model Registry (versioning, state management, and lineage) and Model Monitoring & Drift Detection.
• 3+ years of experience in MLOps or high-scale Software Engineering with a focus on AI production environments.
• Technical Stack Mastery: Expert-level Python and deep experience with container orchestration (Kubernetes, Docker) and cloud infrastructure (AWS/GCP).
• AI Tooling & Frameworks: Proficiency with orchestration libraries (e.g., LangChain, LlamaIndex, CrewAI), vector databases (e.g., Pinecone, Weaviate), and inference engines (e.g., vLLM, TGI).
• Agility & Adaptability: The ability to learn and implement new technologies in a field that changes weekly. You should be a "fast mover" who enjoys constant evolution.
• Software Excellence & Governance: Strong fundamentals in API design, microservices, and "GitOps" methodologies, including the implementation of automated security and compliance by default.
• English Proficiency: Excellent communication skills (minimum C1 level), with the ability to articulate technical vision to both engineers and leadership.

What We Offer 🥁

• Competitive compensation, both in terms of base salary as well as equity plans that enable to you to share in our success
• Flexibility in ways of working both in terms of your schedule as well as your location, whether you prefer to work from home, the office, or abroad with access to a global network of co-working spaces 
• Generous paid time off schemes, including vacation, sabbatical, religious observance and compensation days
• Meaningful benefits including private healthcare coverage, fitness and wellness programs covered through Wellhub, working-from-home allowances to help you set up your home office and cover monthly expenses
• Professional development with annual training budget for conferences, courses, certifications and access to top market e-learning platforms
• Collaborative environment with multiple offices around the globe, regular team activities and events as well as employee-led resource groups