AI Platform Engineer (m/f/d) 1

WELCOME TO BASF

Digitalization is a true part of BASF's DNA — creating new customer experiences, driving business growth, and making processes more efficient. Global Digital Services drives BASF's digital transformation through innovative, global, high-quality digital products and a strong agile culture, and the Digital Hub Madrid is one of our key global delivery locations. 

We are seeking an AI Architect for BASF's DevHub — the Internal Developer Platform (IDP) used by thousands of engineers and product teams across BASF. DevHub already ships an enterprise AI Gateway (50+ governed models, Entra ID, EU data residency, per-cost-center billing, Grafana observability) and a catalog that is a schema-validated knowledge graph of every product and its infrastructure. As AI Architect, you will own the technical vision and architecture of DevHub's AI capabilities: defining how AI is built, integrated, governed, and scaled across the platform. You will work directly with the Product Manager as the architectural counterpart, shaping the AI roadmap, setting technical standards, and ensuring the team builds the right things the right way. You will treat the platform as a product — designing the systems that serve both humans and agents, with the multi-tenant scoping, cost-tracking, guardrails and governance an enterprise platform demands

RESPONSIBILITIES

• Own the AI architecture. Define and evolve the technical architecture for DevHub's AI capabilities: the AI Gateway, agentic services, retrieval/context pipelines, and platform-AI integration points. Produce and maintain architecture decision records (ADRs) and RFCs that guide the team. 


• Set technical direction for the team. Be the architectural authority on pattern selection, technology choices, and build-vs-buy decisions. Ensure the team applies the right pattern for each problem: deterministic pipelines + structured outputs where outcomes are structured; multi-step/multi-agent orchestration only for genuinely open-ended tasks. 


• Design platform-as-product AI capabilities. Architect reusable building blocks (shared retrieval/"context engine," guardrail and evaluation libraries, MCP/tool layer), scaffolder templates, SDK/API surfaces, and stable versioned interfaces — designed once, reused across features and teams. 


• Architect for humans and agents. Design the MCP / SDK / API surface that exposes platform capabilities — read-first, RBAC- and tenant-aware — so internal and external AI clients can query and (later, gated) act on the platform. 


• Drive evaluation and quality standards. Define the evaluation framework: eval harnesses, golden tests, retrieval-quality metrics, grounding and hallucination controls. Establish context engineering as the primary lever over model selection — the Gateway already solves model choice. 


• Shape MLOps / LLMOps practices. Design the path from experiment to production: prompt/version management, model adaptation pipelines, CI/CD for AI artefacts. Ensure prompts and retrieval are treated as versioned, tested production assets. 


• Architect for multi-tenancy and governance. Design per-product / per-tenant scoping of context, tools, and actions. Define the observability architecture (OpenTelemetry, Grafana, distributed tracing) and per-product cost/FinOps visibility.


• Ensure platform RBAC (Entra ID / AccessIT), OWASP LLM Top 10 defences, auditability, and BASF / EU AI Act compliance are embedded by design. 


• Mentor and uplift the engineering team. Provide technical leadership and mentorship to the AI engineers. Conduct architecture reviews, pair on complex problems, and raise the team's technical bar. You are not a people manager, but you are the person the team looks to for technical decisions. 


• Represent AI architecture to stakeholders. Engage with Enterprise Architecture, Product Family leadership, and external partners (Databricks, Microsoft) on architectural alignment, technology strategy, and integration patterns. Translate business requirements into technical architecture and vice versa.

QUALIFICATIONS

• Education: BSc or MSc in Computer Science, Software Engineering, AI, or related field.


• Experience: 7+ years in software/platform engineering, including 2-3 years in technical leadership or architecture roles and recent experience in Generative AI and/or AI-driven systems.


• Strong Python expertise and production AI/LLM architecture experience, with a platform mindset and ability to set technical direction.


• Deep experience designing production-scale LLM systems, including RAG architectures, agentic patterns, context engineering, and appropriate use of autonomous agents.


• Strong system design skills for distributed, multi-tenant systems, including API boundaries, data flows, resilience, ADRs, RFCs, and architecture diagrams.


• Experience designing evaluation frameworks for LLM/RAG systems, including eval harnesses, golden tests, retrieval-quality metrics, grounding, and hallucination control.


• Expert-level Python (FastAPI, Pydantic, async) and production-grade API/platform service design.


• Experience designing reusable self-service platform components, templates, SDKs, and golden paths across teams.


• Deep Azure experience, Kubernetes/AKS at scale, Docker, and infrastructure-as-code (HCL/Terraform).


• Experience with PostgreSQL, vector stores such as Azure AI Search, and state management in multi-tenant platforms.


• Knowledge of LLM providers and platforms including OpenAI, Anthropic, Mistral, Azure AI Foundry, Databricks, and MCP.


• Strong understanding of authentication/authorization, RBAC, tenant isolation, guardrails, auditability, OWASP LLM Top 10, and EU AI Act implications.


• Experience mentoring engineers, conducting architecture reviews, setting technical standards, and communicating technical decisions clearly.


• Nice to have: Databricks/Unity Catalog, TypeScript, Grafana, MLflow, FinOps for AI, A2A, agentic development standards, RabbitMQ, Azure Event Grid, and experience working with enterprise architecture and vendor teams. 

WHAT WE OFFER

• A secure work environment because your health, safety and wellbeing is always our top priority.


• Flexible work schedule and Home-office options, so that you can balance your working life and private life.


• Learning and development opportunities


• 25 holiday days per year


• 5 additional days (readjustment)


• A collaborative, trustful and innovative work environment


• Being part of an international team and work in global projects


• Relocation assistance to Madrid provided

At BASF, the chemistry is right

Because we are counting on innovative solutions, sustainable actions, connected thinking and on you, become a part of our formula for success and develop the future with us - in a global team that embraces diversity and equal opportunities irrespective of gender, age, origin, sexual orientation, disability or belief.At BASF, we are committed to upholding and ensuring compliance with company standards related to quality, environment, health, safety, and energy, in line with our global guidelines.We actively promote a culture of prevention and continuous improvement, encouraging collaboration in initiatives related to quality, environmental protection, health, safety, and energy performance.We foster responsible energy use, promoting efficiency in daily operations and supporting the identification of improvement projects and energy-saving opportunities