AI Engineering Leadership

beBeeAgencification; Barcelona; Híbrido; EUR 80.000 - 150.000; Jornada completa

Descripción de la vacante

A technology-driven company in Barcelona seeks an AI Lead Engineer to architect solutions for a core intelligence platform. The role involves developing AI/ML systems, building cloud infrastructure on AWS, and collaborating with clients in the pharma and automation sectors. Candidates should have strong experience with LLMs, knowledge graphs, and modern AI tooling. Competitive compensation and a flexible work environment are offered.

Servicios

Meaningful equity stake

Flexible work setup

Learning budgets and access to conferences

Formación

• 5+ years of experience in AI / ML system development in production-grade environments.
• 5+ years in AWS cloud infrastructure.
• Strong experience with LLMs and RAG pipelines.

Responsabilidades

• Shape design and delivery of core intelligence layer.
• Build cloud-based infrastructure on AWS.
• Collaborate with clients to translate requirements.

Conocimientos

Experience architecting and developing AI / ML systems

Cloud infrastructures on AWS

Experience with LLMs and RAG pipelines

Proficiency in Python and JavaScript

Knowledge graph design

Experience with retrieval systems

Containerized environments (Docker/Kubernetes)

Clear communication skills

Herramientas

LangGraph

LangChain

PyTorch

TensorFlow

OpenAI APIs

Hugging Face

Descripción del empleo

AI Lead Engineer

About Us

We're building the control layer for agentic automation to govern the workforce of the future.

Our technology translates regulatory and operational directives drawn from SOPs, policies, and best practices into structured guidance for intelligent agents.

The rules are encoded into retrieval-augmented knowledge graphs that integrate seamlessly into any language model.

The problem : companies spend up to 25% of their revenue on compliance – training, audits, documentation – yet failures remain rampant. We're replacing the compliance function itself with a real-time control layer that governs AI agents on the ground.

The first strong pull comes from healthcare, especially the pharmaceutical industry, where thousands of legacy SOPs still govern mission-critical processes. These rules are vital to ensuring quality, traceability, and ultimately, patient safety.

About the Role

AI Solution Architect

You will shape the design and delivery of the core intelligence layer behind our platform. From encoding complex regulatory rules into structured knowledge graphs to embedding them in next-gen LLM-based agents, you'll architect and engineer solutions that are foundational to how our technology scales across industries.

You'll work end-to-end—from high-level system design to hands-on development bridging deep AI architecture, product thinking, and enterprise integration. This role is ideal for someone ready to take ownership of technical direction, shape infrastructure from the ground up, and make real-time decisions that impact clients, models, and the product itself.

• Strategic Planning and Roadmap Development
• Architect and build the data and AI cloud-based infrastructure on AWS
• Architect and build RAG pipelines that translate regulatory content (SOPs, policies, standards) into structured knowledge graphs and control logic leveraging AI
• Develop real-time orchestration patterns to embed this logic into agent frameworks such as LangGraph, LangChain, CrewAI, and Autogen
• Design scalable and modular components using vector databases, graph databases, semantic search, and transformer-based models
• Own the decision-making process around system architecture, data pipelines, model integration, and retrieval strategies
• Collaborate with enterprise clients and internal teams to translate abstract requirements into robust AI-driven compliance layers
• Prototype, validate, and iterate quickly in an agile, feedback-driven environment
• Influence and evolve our AI platform's technical strategy, working closely with product and engineering stakeholders

Qualifications & Requirements

Must-Haves :

5+ years of experience architecting and developing AI / ML systems in a production-grade environment, preferred in regulated settings

5+ years of experience in cloud infrastructures on AWS, leveraging services such as Sagemaker, DynamoDB, DocumentDB, Textract, Kendra, Bedrock, Neptune, etc.

Strong experience with LLMs, RAG pipelines, and knowledge graph design

Proficiency in modern AI / ML tooling : Python, JavaScript, LangGraph, LangChain, PyTorch, TensorFlow, OpenAI APIs, Hugging Face, etc.

Deep understanding of retrieval systems, semantic embeddings, vector databases (e.g., FAISS, Weaviate, Pinecone), and orchestration frameworks

Ability to translate complex, domain-specific rules into formalized, machine-readable logic

Experience designing scalable containerized environments (Docker / Kubernetes)

Clear, confident communicator who can collaborate cross-functionally and work directly with clients

Bonus Points :

Familiarity with tools for parsing and processing long-form documents (e.g., PDF mining, OCR, NLP pipelines)

Background in knowledge representation, ontology engineering, or symbolic AI

Open-source contributions or published research in relevant fields

Exposure to agent orchestration frameworks (e.g., CrewAI, Autogen, Semantic Kernel)

Benefits

Competitive compensation with a meaningful equity stake

Founding-tier influence in a deep tech company with real enterprise traction and massive upside potential

Flexible work setup

Work alongside a high-caliber team of engineers, researchers, and operators obsessed with building AI that works in production

Opportunity to evolve into a key leadership position as we scale

Direct exposure to industry-defining challenges in Pharma, MedTech, and enterprise automation

Access to conferences, learning budgets, and the tools you need to stay ahead of the curve

The Stack You'll Touch

LangGraph, LangChain, CrewAI, Autogen, OpenAI APIs, LlamaIndex

Python, JavaScript, FastAPI, Neo4j, FAISS, Weaviate

AWS, Docker, Postgres, GitHub Copilot, Notion

REMUNERATION_MIN : 80000

REMUNERATION_MAX : 150000

REMUNERATION_CURRENCY : EUR