SVP of Engineering
Job Description
Explicitly calls out "vibe coding" and adoption of AI-assisted dev tools (Copilot, Claude Code, Cursor) for rapid prototyping and improved developer experience.
About the Role\nSenior technology leader to serve as SVP/CTO for SymphonyAI’s Supply Chain Division in EMEA, responsible for driving a multi-year transformation from legacy on-premise systems to a cloud-native, AI-first composable SaaS platform. Lead platform architecture, large engineering teams (150–300+), generative AI integration, client-facing technology engagements, and technical M&A decisions.
Job DescriptionRole\nSymphonyAI is hiring an SVP of Engineering / EMEA CTO for its Supply Chain Division to lead a transformation mandate: move a legacy, on-prem supply chain platform to a cloud-native, composable SaaS architecture and embed AI/ML and generative AI across the product suite. The role is based in EMEA (Paris headquarters) and includes global engineering leadership and client-facing responsibilities.
Key Responsibilities\n- \n
- Define and own the multi-year roadmap for Systems of Execution (WMS, TMS, OMS) and Systems of Intelligence (demand planning, supply optimization, decision analytics). \n
- Architect transformation from monolithic legacy systems to composable, API-first, cloud-native SaaS using microservices and event-driven design. \n
- Embed AI/ML as a foundational design principle and integrate generative AI/LLMs for copilots, natural language interfaces, autonomous workflows, and agentic capabilities. \n
- Own technical due diligence for M&A, partnerships, and build-vs-buy decisions. \n
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- Build and scale engineering organization across Paris and global centers (target 150–300+ engineers). \n
- Establish CI/CD, automated testing, IaC, feature flagging, canary deployments, and observability-first culture. \n
- Drive metrics for deployment frequency, lead time, MTTR, change failure rate; implement platform reliability standards (target 99.95%+ uptime, SOC 2 Type II, GDPR/data sovereignty). \n
- Champion developer experience and AI-assisted development tools (e.g., Copilot, Claude Code, Cursor) and rapid prototyping workflows. \n
- Lead applied AI strategy for forecasting, inventory optimization, routing, supplier risk, and digital twins. \n
- Deploy generative AI across product features (LLM assistants, automated reporting, anomaly explanation, conversational analytics). \n
- Build agentic AI frameworks for autonomous supply chain actions and integrate privacy-preserving and sandboxing patterns. \n
- Run an innovation lab for rapid POCs with clients and productize successful experiments within ~90-day cycles. \n
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- Serve as senior technology executive in strategic engagements with large retailers and CPG enterprises; present to CIOs/CTOs/CDOs. \n
- Lead technical strategy in deal pursuits, RFPs, proof-of-value, and contract renewals; co-create roadmaps with strategic accounts. \n
- Represent the company at industry conferences and analyst briefings. \n
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- Lead data model modernization, API gateway design, tenant isolation, and migration strategies for enterprise clients (parallel runs, phased cutovers). \n
- Modernize data architecture to support real-time streaming and graph-based modeling (Kafka, Flink) and unified analytics for operations and ML training. \n
- Transition release management from quarterly waterfall to continuous deployment with feature flags while protecting enterprise stability. \n
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- Partner with the CEO on division strategy, planning, budgeting, and investment priorities. \n
- Align technology investments with market demand and ARR growth; own technology budget and resource allocation. \n
- Build a diverse engineering culture and chair a Technical Advisory Board of external supply chain and AI experts. \n
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- 15+ years in enterprise software engineering and technology leadership; at least 5 years at VP/SVP/CTO level in supply chain, retail, or CPG technology. \n
- Deep domain expertise across System of Execution and System of Intelligence components of supply chain. \n
- Proven track record leading platform transformation from on-prem to cloud-native SaaS at enterprise scale (100+ enterprise clients, $50M+ ARR platform). \n
- Direct experience delivering production-grade, customer-facing AI/ML capabilities at scale. \n
- Familiarity with competitive supply chain platforms and experience working with retailers/CPG clients. \n
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- Strong architectural fluency: microservices, API-first, event-driven architecture, multi-tenant isolation, Kubernetes/container orchestration, serverless patterns. \n
- Working knowledge of cloud data platforms (Snowflake, Databricks, BigQuery, Azure Synapse) and real-time streaming (Kafka, Flink, Spark Streaming). \n
- Familiarity with generative AI patterns (LLM fine-tuning, RAG, prompt engineering, function calling, agent frameworks) and graph/knowledge graph technologies. \n
- DevOps/SRE practices at scale: CI/CD, IaC (Terraform, Pulumi), observability (Datadog, Grafana), incident management. \n
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- Builder mentality with hands-on orientation; executive presence and strong communication skills; collaborative and bias for action; comfort with ambiguity. \n
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- Experience at leading supply chain technology vendors or major retailers/CPG companies. \n
- Prior experience with data monetization, retail media intersection, outcome-based pricing, and multi-geography engineering organizations. \n
- Fluent in French and English; advanced quantitative degree (MS/PhD) a plus. \n
Technology Vision System Architecture Cloud Migration AI Strategy ML/AI Productionization MLOps Microservices Event-driven Architecture DevOps/SRE CI/CD Infrastructure as Code Observability Incident Management Data Architecture Streaming Systems Client-facing Communication Stakeholder Management M&A Technical Due Diligence Organizational Leadership Change Management
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