Ai Lead Engineer

Playbook®; España; Híbrido; EUR 60.000 - 80.000; Jornada completa

Descripción de la vacante

A technology firm in Spain seeks an AI Solution Architect to shape the core intelligence layer of their platform. The role demands extensive experience in AI/ML systems, AWS cloud services, and expertise with LLMs. Ideal candidates will bridge AI architecture and product thinking while influencing the platform's technical strategy. The position offers competitive salary, equity, and flexible work options.

Servicios

Competitive salary with equity stake

Flexible work setup—remote/hybrid options

Access to conferences and learning budgets

Formación

• Minimum 5 years of experience in AI/ML systems in production, preferably in regulated settings.
• Strong expertise with LLMs, RAG pipelines, and knowledge graph design.
• Excellent communication skills for cross-functional collaboration.

Responsabilidades

• Strategic Planning and Roadmap Development.
• Architect and build cloud-based infrastructure on AWS.
• Develop RAG pipelines translating regulatory content into knowledge graphs and control logic.
• Prototype, validate, and iterate quickly in an agile environment.

Conocimientos

AI/ML systems experience

AWS cloud infrastructure

Expertise with LLMs

Proficiency in Python

Understanding of retrieval systems

Designing scalable environments

Excellent communication skills

Herramientas

LangGraph

LangChain

PyTorch

TensorFlow

Docker

Descripción del empleo

About Playbook:

At Playbook, we're building the control layer for agentic automation to govern the workforce of the future. We enable companies to inject rule-based behavior into autonomous AI agents by translating regulatory and operational directives—drawn from SOPs, policies, and best practices—into structured guidance. These rules are encoded into retrieval-augmented knowledge graphs that seamlessly integrate into any language model.

The problem:

Companies today spend up to 25% of their revenue on compliance activities like training, audits, and documentation, yet failures are still common. We aim to eliminate that overhead by replacing the compliance function with a real-time control layer that governs AI agents on the ground. Our initial focus is on healthcare, especially the pharmaceutical industry, where legacy SOPs govern critical processes vital for quality, traceability, and patient safety.

Founded in 2022, Playbook is a post-revenue company serving over 1000 quality leaders in pharma and MedTech. We are a team of 22 (including 12 engineers), backed by leading VCs like Capnamic and 14 Peaks Capital, with recent seed funding in Q1 2025.

About the Role:

AI Solution Architect: As our AI Lead Engineer, you will shape the design and delivery of the core intelligence layer behind Playbook's platform. Your work will include encoding complex regulatory rules into structured knowledge graphs and embedding them into next-gen LLM-based agents. You will architect and engineer solutions that are foundational for scaling our technology across industries, working from system design to hands-on development—bridging AI architecture, product thinking, and enterprise integration. This role is ideal for someone eager to take ownership of technical direction, shape infrastructure, and make impactful decisions affecting clients, models, and products.

What You’ll Do:

1. Strategic Planning and Roadmap Development
2. Architect and build cloud-based infrastructure on AWS
3. Develop RAG pipelines translating regulatory content into knowledge graphs and control logic
4. Design real-time orchestration patterns for agent frameworks like LangGraph, LangChain, CrewAI, Autogen
5. Create scalable, modular components using vector databases, graph databases, semantic search, and transformers
6. Own decision-making around system architecture, data pipelines, model integration, and retrieval strategies
7. Collaborate with clients and internal teams to translate requirements into AI-driven compliance layers
8. Prototype, validate, and iterate quickly in an agile environment
9. Influence and evolve the platform’s technical strategy with product and engineering teams

Qualifications & Requirements:

• Minimum 5 years of experience in AI/ML systems in production, preferably in regulated settings
• At least 5 years of experience with AWS cloud infrastructure (Sagemaker, DynamoDB, etc.)
• Strong expertise with LLMs, RAG pipelines, and knowledge graph design
• Proficiency in Python, JavaScript, LangGraph, LangChain, PyTorch, TensorFlow, OpenAI APIs, Hugging Face
• Deep understanding of retrieval systems, semantic embeddings, vector databases (FAISS, Weaviate, Pinecone), and orchestration frameworks
• Experience translating complex rules into formalized logic
• Designing scalable containerized environments (Docker/Kubernetes)
• Excellent communication skills for cross-functional collaboration

Bonus Points:

• Experience with document parsing, OCR, NLP pipelines
• Background in knowledge representation, ontology engineering, or symbolic AI
• Open-source contributions or published research
• Exposure to agent orchestration frameworks like CrewAI, Autogen

Perks & Compensation:

• Competitive salary with equity stake
• Influence in a deep tech company with enterprise traction and growth potential
• Flexible work setup—remote/hybrid options
• Work with a high-caliber team of engineers and researchers
• Opportunities for leadership and industry impact
• Access to conferences, learning budgets, and essential tools

The Stack You’ll Touch:

• LangGraph, LangChain, CrewAI, Autogen, OpenAI APIs, LlamaIndex
• Python, JavaScript, FastAPI, Neo4j, FAISS, Weaviate
• AWS, Docker, Postgres, GitHub Copilot, Notion