Senior MLE Staff Engineer (GenAI Platform)
AI Tools
Tech Stack
Agent Workflow
Building specialized infrastructure to support long-running agentic workflows, including state management, tool-calling interfaces, and complex reasoning loops. Multi-agent architecture support with production evaluation and observability.
About the Role
Senior MLE Staff Engineer (GenAI Platform)
Clarity AI
Madrid, Spain (Remote/Hybrid, CET +/- 2 hours)
About the Company
Clarity AI, founded in 2017, is a sustainability-focused tech firm with 300+ employees across five global offices. The organization leverages AI to help investors, governments, and companies make informed decisions. Major backers include BlackRock, SoftBank, and Deutsche Borse. The company emphasizes a fact-based, diverse, transparent, meritocratic, and flexible workplace culture.
Key Responsibilities
The role bridges ML experimentation and production by
- GenAI Platform Engineering: Design systems for deploying LLMs and multi-agent solutions
- Agent Infrastructure: Build systems supporting long-running workflows with state management, tool-calling interfaces, and complex reasoning loops
- Model Serving: Scale inference globally while optimizing latency, throughput, and costs
- Deployment Pipeline: Establish self-service pathways with automated evaluation, safety guardrails, CI/CD/CT pipelines, observability for hallucinations and RAG performance, and model registry management
- Strategic Evolution: Monitor AI trends and upgrade platform capabilities continuously
- Observability: Implement unified monitoring across data, ML, and GenAI layers
- Enablement: Provide tools helping data scientists move from models to production services
- Design prompt lifecycle management, LLM abstraction layers, and cost controls
Required Qualifications
- 3+ years MLOps or AI production engineering experience
- Deep hands-on experience deploying LLMs and complex agentic architectures at scale
- Expert-level evaluation frameworks (Ragas, DeepEval, G-Eval) with LLM-as-a-judge patterns
- Expertise in prompt lifecycle management, LLM abstraction layers, cost controls
- Model registry and drift detection understanding
- Expert Python; Kubernetes/Docker mastery
- AWS/GCP cloud infrastructure experience
- Orchestration tools (LangChain, LlamaIndex, CrewAI); vector databases; inference engines (vLLM, TGI)
- API design, microservices, GitOps fundamentals
- C1-level English fluency
Compensation & Benefits
- Competitive base salary plus equity participation
- Flexible scheduling and location options
- Generous PTO including sabbatical options
- Healthcare, wellness programs, home office allowances
- Annual professional development budget
- Global collaborative environment
