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Position Overview

The Director, Agentic AI & Code Generation Platforms (SD) is the executive leader and key stakeholder for our enterprise agentic AI and developer productivity platforms. The SD sets the vision and drives outcomes for how autonomous AI agents, code-generation capabilities, and platform engineering unlock business value across product lines. This role aligns AI platform strategy with customer needs, measurable ROI, and responsible AI principles—ensuring teams have clear problem statements, prioritized backlogs, and secure, scalable foundations to deliver complete, performant, and durable solutions. The SD provides repeatable, high-clarity content and enablement for squads, product teams, and executives, and brings deep fluency in Agile/Lean, Platform Engineering, MLOps, SRE, Continuous Delivery, Cloud, Containers/Kubernetes, and compliance-by-design.

Responsibilities

·       Strategy & Vision: Define and socialize the multi-year strategy for agentic AI and code-generation platforms, including architectural north stars, capability maps, and business-value hypotheses (OKRs, KPIs). Establish 'platform as a product' practices—clear service catalogs, SLAs/SLOs, roadmaps, and customer-obsessed discovery with product teams.

·       Product & Platform Roadmaps: Own quarterly/annual roadmaps that balance functional features (agent orchestration, tool integrations, secure function-calling/RAG pipelines, IDE plugins) with non-functional requirements (security, privacy, safety, resilience, observability, cost). Ensure platform roadmaps consistently account for compliance, security, operations, performance, and data governance from inception to run.

·       Engineering Excellence (Agile, DevEx, SRE, CD): Lead high-performing platform engineering and SRE squads practicing Agile/Lean, trunk-based development, CI/CD, progressive delivery, and 'you build it, you run it.' Drive improvements to source control, build systems, deployment pipelines, operations, maintenance, cost controls/FinOps, security tooling, monitoring/alerting/traceability, and audit readiness. Maintain a 24×7, global, highly-available SaaS environment aligned to internal/external SLAs/SLOs and error budgets; provide executive escalation for major incidents and post-mortem learning.

·       Agentic AI & Code Generation Enablement: Architect and productize agent runtimes, tool/plugin ecosystems, secure function-calling, retrieval-augmented generation (RAG), and policy enforcement layers (guardrails, content filters, privacy controls). Advance developer productivity with code-generation assistants (pair-programming, test generation, refactoring), documentation synthesis, and automated remediation—measuring real ROI on cycle time and defect escape rates.

·       Agentic Experimentation & Innovation: Foster a culture of experimentation with agentic workflows, autonomous orchestration, and adaptive reasoning systems; establish safe sandboxes for rapid prototyping and evaluation.

·       Quality Engineering & Developer Experience: Institutionalize specification-driven development, error analysis, and behavior-driven design (BDD) practices across platform teams. Ensure automated test generation, documentation synthesis, and traceability for compliance and reliability.

·       Data/ML Platform & LLMOps: Partner with Data/ML leaders to operationalize model lifecycle (evaluation, deployment, monitoring), feature stores, vector indices, prompt and policy libraries, and red-team/testing frameworks for safety/quality. Govern model usage (internal/third-party) with clear standards for security, compliance, provenance, and cost/performance trade-offs.

·       Stakeholder Engagement & Adoption: Engage clients, product managers, and engineering leaders to discover needs, shape backlog intent ('what' and 'why'), and drive adoption of platform capabilities through playbooks, workshops, and internal marketplaces. Provide coaching and conflict resolution on features/requirements; deliver executive-level narratives that connect technical investments to business outcomes.

·       Financials, Vendor & Partnership Management: Own platform budgets, FinOps guardrails, and cost-to-serve models; negotiate vendor contracts and partnerships (cloud, tooling, data/ML) aligned to strategic outcomes and risk posture.

·       Risk, Compliance & Responsible AI: Institute Responsible AI governance (fairness, robustness, transparency, privacy), security baselines, and regulatory readiness (e.g., data residency, audit trails, model risk). Ensure production systems operate per established procedures and best practices; champion secure-by-default controls and continuous compliance.

·       Talent & Culture: Build and mentor a diverse, high-performing organization; set standards for technical excellence, psychological safety, and continuous improvement. Lead succession planning, career frameworks, and competency matrices for platform engineering, SRE, and AI/ML roles.

Required Knowledge/Skills, Education, and Experience

Knowledge/Skills

·       Expert in Agile/Lean, platform engineering, SRE, and continuous delivery.

·       Deep experience with cloud platforms, Kubernetes, IaC, observability, and incident/post-mortem practices.

·       GenAI stack familiarity preferred (LLMs, orchestration frameworks, vector databases, prompt/policy libraries).

·       Agentic experimentation desired—experience designing and validating autonomous agent workflows.

·       Strong awareness of AI/ML fundamentals, Information Retrieval (IR) techniques, and retrieval-augmented generation (RAG) pipelines.

·       Proven ability in error analysis, specification authoring, documentation, and test writing using BDD-driven design principles.

·       Executive communication and stakeholder management skills.

Education

BA/BS in Computer Science or related field required; MS/MBA preferred.

Experience

12–15+ years in software/product/platform engineering with 5–8+ years leading managers and cross-functional teams; prior experience owning enterprise platforms and/or large AI initiatives.

This position will be subject to U.S. export control requirements under the International Traffic in Arms Regulations (ITAR) and/or Export Administration Regulations (EAR).  Employment is contingent on either verifying the U.S. Person status or obtaining any necessary export license.  

Why us?

Working at Siemens Software means flexibility - Choosing between working at home and the office at other times is the norm here. We offer great benefits and rewards, as you'd expect from a world leader in industrial software.

A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow!

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