Job Description
Job Title: Senior Vice President (SVP) – Generative AI & Software Backend Engineering
Experience: 18+ Years
Location: Open / Hybrid / Global
Reports to: CTO / CEO
The Opportunity
We’re seeking a rare hybrid leader—someone who speaks LLMs and system design with equal fluency. As SVP – Gen AI & Software Backend Engineering, you will define the technology backbone of the company, owning both next-gen AI innovation and planet-scale backend platforms.
This role sits at the core of the CTO’s office and shapes how AI is imagined, built, shipped, and scaled.
What You’ll Lead & Own
1. Gen AI Strategy & AI Platform Leadership
- Define the enterprise-wide Generative AI vision and roadmap—from copilots to autonomous agents.
- Architect and scale LLM-powered systems including RAG pipelines, vector databases, agentic workflows, and multimodal AI.
- Drive AI platformization to enable rapid experimentation and safe production rollout across teams.
- Establish Responsible AI, governance, security, and cost controls for large-scale AI adoption.
2. Backend Engineering at Scale
- Own the design and evolution of high-performance backend systems powering AI-first products.
- Lead architecture for microservices, event-driven systems, APIs, data platforms, and distributed systems.
- Ensure reliability, scalability, observability, and performance across cloud-native platforms.
- Champion engineering excellence—clean architecture, design reviews, and system thinking.
3. Product, Business & Execution
- Partner with Product, Data, and Business leaders to translate AI capabilities into real customer value and revenue.
- Balance innovation vs. operability—making sure cutting-edge tech actually ships and scales.
- Own delivery of 0→1 platforms and 1→100 enterprise systems.
4. Leadership & Culture
- Build and mentor elite AI and backend engineering teams across geographies.
- Set the bar for technical rigor, velocity, and ownership.
- Act as a technical sounding board for the CTO, exec team, and board.
What You Bring
- 18+ years of experience in software engineering and technology leadership
- Deep backend engineering pedigree with strong fundamentals in:
- Distributed systems & system design
- Microservices, APIs, data stores, and event streaming
- Cloud platforms (AWS / Azure / GCP)
- Hands-on and strategic experience in Generative AI, including:
- LLMs, RAG, embeddings, vector databases
- Agentic AI systems and AI orchestration
- Model inference optimization & MLOps
- Proven success leading large, high-impact engineering orgs
- Ability to operate seamlessly between whiteboard architecture, code reviews, and boardroom strategy
Tech Stack Exposure (Indicative)
- Backend: Java, Go, Python, Node.js
- AI/ML: Open AI, Anthropic, Gemini, open-source LLMs (LLa MA, Mistral), Lang Chain, Llama Index
- Data: Kafka, Redis, Postgre SQL, No SQL, Vector DBs
- Cloud & Infra: Kubernetes, Docker, Terraform, CI/CD
- (Tools may vary—the thinking matters more than the stack)
What Makes This Role Special
- You own both AI intelligence and system foundation
- Influence company strategy, not just architecture
- Build platforms that define the future, not features
- Work with leadership that treats AI + Engineering as a competitive moat
Nice to Have (Not Mandatory)
- Experience in AI-first or platform companies
- Exposure to regulated or large-scale enterprise systems
- Prior role as SVP / VP Engineering / Head of Platform / Head of AI
Experience: 18+ Years
Location: Open / Hybrid / Global
Reports to: CTO / CEO
The Opportunity
We’re seeking a rare hybrid leader—someone who speaks LLMs and system design with equal fluency. As SVP – Gen AI & Software Backend Engineering, you will define the technology backbone of the company, owning both next-gen AI innovation and planet-scale backend platforms.
This role sits at the core of the CTO’s office and shapes how AI is imagined, built, shipped, and scaled.
What You’ll Lead & Own
1. Gen AI Strategy & AI Platform Leadership
- Define the enterprise-wide Generative AI vision and roadmap—from copilots to autonomous agents.
- Architect and scale LLM-powered systems including RAG pipelines, vector databases, agentic workflows, and multimodal AI.
- Drive AI platformization to enable rapid experimentation and safe production rollout across teams.
- Establish Responsible AI, governance, security, and cost controls for large-scale AI adoption.
2. Backend Engineering at Scale
- Own the design and evolution of high-performance backend systems powering AI-first products.
- Lead architecture for microservices, event-driven systems, APIs, data platforms, and distributed systems.
- Ensure reliability, scalability, observability, and performance across cloud-native platforms.
- Champion engineering excellence—clean architecture, design reviews, and system thinking.
3. Product, Business & Execution
- Partner with Product, Data, and Business leaders to translate AI capabilities into real customer value and revenue.
- Balance innovation vs. operability—making sure cutting-edge tech actually ships and scales.
- Own delivery of 0→1 platforms and 1→100 enterprise systems.
4. Leadership & Culture
- Build and mentor elite AI and backend engineering teams across geographies.
- Set the bar for technical rigor, velocity, and ownership.
- Act as a technical sounding board for the CTO, exec team, and board.
What You Bring
- 18+ years of experience in software engineering and technology leadership
- Deep backend engineering pedigree with strong fundamentals in:
- Distributed systems & system design
- Microservices, APIs, data stores, and event streaming
- Cloud platforms (AWS / Azure / GCP)
- Hands-on and strategic experience in Generative AI, including:
- LLMs, RAG, embeddings, vector databases
- Agentic AI systems and AI orchestration
- Model inference optimization & MLOps
- Proven success leading large, high-impact engineering orgs
- Ability to operate seamlessly between whiteboard architecture, code reviews, and boardroom strategy
Tech Stack Exposure (Indicative)
- Backend: Java, Go, Python, Node.js
- AI/ML: Open AI, Anthropic, Gemini, open-source LLMs (LLa MA, Mistral), Lang Chain, Llama Index
- Data: Kafka, Redis, Postgre SQL, No SQL, Vector DBs
- Cloud & Infra: Kubernetes, Docker, Terraform, CI/CD
- (Tools may vary—the thinking matters more than the stack)
What Makes This Role Special
- You own both AI intelligence and system foundation
- Influence company strategy, not just architecture
- Build platforms that define the future, not features
- Work with leadership that treats AI + Engineering as a competitive moat
Nice to Have (Not Mandatory)
- Experience in AI-first or platform companies
- Exposure to regulated or large-scale enterprise systems
- Prior role as SVP / VP Engineering / Head of Platform / Head of AI
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