Development Architect

About the company

What you'll bring You’ll join Applied AI Builders, a small, hands-on pod that works closely with the CTO for Industry AI ENR. Our job is to take ambiguous problems, half-formed ideas, and evolving initiatives, and turn them into prototypes, proofs, and production-ready outcomes. Some weeks we’re embedded with a product team, partnering on a specific AI mission. Other weeks we’re stress-testing a raw idea to see whether it deserves to be built, adapted, or respectfully retired. If you need stable, well-defined requirements before you can start, this pod will be uncomfortable. If ambiguity feels like oxygen and you’d rather supervise an AI than trust it, keep reading.

Your tasks

What you'll build

• 12+ years of experience in prototype-to-production spectrum: we build fast, validate honestly, and partner with platform and product teams to scale what proves valuable.
• The stack varies — Python, TypeScript, Terraform, BTP, Joule Studio, CAP, Fiori, whatever the mission needs — but we care far more about your taste for good code, your ability to supervise Claude-style code generators and AI brainstormers, and your architectural judgment than about fluency in any single language.
• You’ll use tools like Claude as accelerators, but you’ll read what they produce, challenge their choices, and know when the AI is making the wrong call — both in code and in idea generation.
• You will build and own the architectures, guardrails, and evaluation strategies for our most important missions — including ontology-driven agents and their comparison to prompt-based systems. You’ll decide, with evidence, which initiatives to scale, adapt, hand back to product teams for adoption, or retire with a well-argued rationale.

Where you belong The pod’s missions sit at the frontier of AI-native engineering. One current mission: ontologies. We’re designing and evolving ontologies for our domains, building agents on top of them, and proving — with data — how ontology-grounded agents compare to raw prompt-and-MCP-based agents. We’re defining the evaluation methodology that makes that comparison honest. This is one mission of many; more will follow as we double-click into AI engineering. You will be the technical anchor for Applied AI Builders — mentoring other builders in the pod, partnering with the CTO for Industry AI ENR on hard investment calls, and setting the bar for what good AI-native engineering looks like in our org. A good seat for a strong individual contributor who wants broader technical influence without moving into full-time management.

Requirements

Four values show up at every level of this team:

• Learning agility (non-negotiable, and the most important value in this pod) — you rapidly pick up new models, frameworks, SAP technologies, ontologies, and industry processes. You enjoy updating your mental model as the landscape shifts, which it will, frequently.
• Bias for action — you move quickly from ambiguity to a working prototype and learn through execution.
• Critical thinking — you ask the right questions, so we stay focused on the objective instead of just managing the day.
• End-to-end ownership — you own the outcome from problem definition through build, deployment, and evaluation.

Deep experience architecting AI-native systems (LLMs, advanced RAG, multi-agent, ontology-grounded agents) and running them on SAP BTP at scale. Strong on eval strategy, benchmarking, and guardrails. Adept at supervising Claude-style generators for architecture, code, and ideas — you set the tone for what good design means on a team that codes and thinks with AI every day. Governance, security, and privacy are things you factor in from the start.