Senior Vice President (SVP) – Agentic AI & Orchestration Engineering
Location
Germany/India
Experience
17–25 Years
Role Overview
We are looking for a visionary and execution-focused Senior Vice President (SVP) – Agentic AI & Orchestration Engineering to lead the strategy, architecture, and delivery of next-generation AI platforms powered by multi-agent systems, orchestration frameworks, LLM applications, and autonomous workflows.
This role requires a strong blend of engineering leadership, AI/ML expertise, platform thinking, enterprise architecture, and organizational scaling experience. The ideal candidate will drive the development of scalable agentic AI ecosystems that enable intelligent automation across enterprise functions including engineering, customer operations, analytics, product, and business workflows.
The SVP will lead large global engineering organizations, define AI platform roadmaps, establish governance frameworks, and collaborate closely with Product, Data Science, Infrastructure, Security, and Executive Leadership teams.
Key Responsibilities
Strategic Leadership
- Define and drive enterprise-wide vision for Agentic AI, multi-agent systems, orchestration platforms, and autonomous enterprise workflows.
- Build long-term roadmap for AI-native platform capabilities including reasoning engines, memory systems, tool integrations, planning agents, and workflow orchestration.
- Partner with executive leadership to align AI initiatives with business transformation goals.
- Drive innovation in enterprise AI adoption, operational automation, and intelligent decision-making systems.
Engineering & Architecture Leadership
- Lead architecture and development of scalable multi-agent AI platforms and orchestration systems.
- Oversee design of AI infrastructure supporting:
- LLM orchestration
- AI agents
- RAG pipelines
- Vector databases
- AI workflow engines
- Tool calling frameworks
- Knowledge systems
- AI observability
- Drive adoption of cloud-native and distributed systems architecture.
- Establish best practices for AI platform scalability, resiliency, security, governance, and reliability.
AI & Agentic Systems
- Lead implementation of autonomous AI agents capable of reasoning, planning, memory management, and tool execution.
- Build enterprise orchestration capabilities across multiple AI agents and business systems.
- Define standards for:
- Agent collaboration
- Context sharing
- Human-in-the-loop workflows
- AI safety & compliance
- Prompt engineering
- Evaluation frameworks
- Drive innovation in advanced AI areas including:
- Multi-agent collaboration
- Autonomous workflows
- AI copilots
- Conversational AI
- Enterprise knowledge intelligence
Organizational Leadership
- Build and scale high-performing global engineering organizations.
- Lead multiple Directors, Engineering Managers, Principal Engineers, Architects, and AI research teams.
- Establish engineering culture focused on innovation, execution excellence, ownership, and continuous learning.
- Mentor senior technology leaders and create succession planning for critical leadership roles.
Delivery & Execution
- Drive large-scale enterprise AI programs from concept to production deployment.
- Ensure predictable delivery, operational excellence, and measurable business outcomes.
- Establish KPIs and governance for AI platform adoption, performance, and reliability.
- Manage cross-functional stakeholder alignment across Product, Business, Operations, Security, and Infrastructure teams.
Governance, Risk & Compliance
- Establish responsible AI governance models and compliance frameworks.
- Ensure enterprise-grade security, privacy, auditability, and ethical AI practices.
- Drive AI observability, monitoring, and model evaluation standards.
- Implement frameworks for risk mitigation, hallucination management, and AI quality assurance.
Required Qualifications
- 17–25 years of experience in software engineering, platform engineering, AI/ML, or enterprise technology leadership.
- Strong experience leading large engineering organizations and managing senior technology leaders.
- Proven expertise in building scalable distributed systems and cloud-native platforms.
- Deep understanding of:
- Agentic AI systems
- AI orchestration frameworks
- LLM ecosystems
- Multi-agent architectures
- Generative AI platforms
- Hands-on exposure to technologies/frameworks such as:
- LangChain / LangGraph
- AutoGen
- CrewAI
- OpenAI Agents SDK
- Vector databases
- RAG architectures
- AI observability platforms
- Strong knowledge of cloud ecosystems including AWS, Azure, or GCP.
- Experience driving enterprise transformation programs and platform modernization initiatives.
- Strong executive communication and stakeholder management capabilities.
Preferred Qualifications
- Experience building enterprise AI products or AI platform organizations at scale.
- Exposure to autonomous systems, workflow automation, or cognitive architectures.
- Understanding of AI governance, compliance, and responsible AI frameworks.
- Experience in product engineering, platform engineering, or enterprise SaaS environments.
- MBA or advanced degree in Computer Science, AI, Engineering, or related fields preferred.
Leadership Expectations
- Strategic thinker with strong execution capabilities.
- Ability to influence executive stakeholders and drive organizational transformation.
- Strong problem-solving and systems-thinking mindset.
- Passion for innovation, experimentation, and emerging AI technologies.
- Ability to operate effectively in fast-paced, high-growth environments.
Success Metrics
- Enterprise AI platform adoption and scalability
- AI-driven automation impact
- Engineering delivery excellence
- Platform reliability and governance maturity
- Talent retention and leadership development
- Business transformation outcomes through AI initiatives
Ideal Background
- Candidates from the following environments would be highly relevant:
- Enterprise AI Platforms
- Large-scale Product Engineering Organizations
- Cloud & Data Platforms
- AI Infrastructure Companies
- Generative AI Startups
- Digital Transformation Organizations
- Autonomous Workflow / Agentic AI Ecosystems
