SVP, Engineering

1 мес. назад

USAC-level

Senior Vice President of Engineering role leading AI-native digital worker development for enterprise intelligence.

Обязанности

The SVP, Engineering is the most senior engineering executive at JazzX—responsible for the platform and application/solution engineering organization, AI systems quality, reliability, and the engineering function that turns the JazzX platform into an enterprise-grade, scalable product. You will lead engineering strategy, architecture, and delivery in close partnership with Product, Customer Delivery, and GTM.
This is a full-stack engineering leadership role with ownership across platform architecture, AI systems, application and solution engineering, infrastructure, security, and organizational scaling. You will define how the platform is built, how quality is measured, how deployments become repeatable, and how JazzX scales across domains, customers, and partners without drifting into bespoke execution.
The engineering leader inherits a live operational platform, a production-deployed mortgage solution as the first wedge in our multi-domain strategy, active customers, and a large pipeline.
Reports To CEO.

Требования

The strongest candidates will combine scaled AI-native engineering leadership, strong architectural judgment, production operations experience, and the ability to build both a platform and the organization required to scale it.

Условия

This is a rare opportunity to define the engineering strategy and organization of a company building an AI-native platform with real customer traction, a live mortgage business, and the ambition to expand into adjacent verticals and partner-led growth. This role is about accelerating a real business, not building from zero.
Own the architecture and engineering organization of a live, production-deployed AI platform—not a prototype.
Drive how JazzX scales across adjacent domains and enables partner-led growth through repeatable platform leverage.
Build a world-class engineering organization across the US and India—with the talent and scope to matter.
True company-level ownership across platform architecture, AI quality, delivery systems, and the engineering org—with enough scope to matter and enough backing to execute.
Early-stage speed paired with the reach, customer access, and operating support of SAI Group.
This is a Bay Area-based executive role, with regular in-person collaboration expected with leadership, customers, and the broader SAI ecosystem. Compensation includes a competitive executive base salary, bonus opportunity, equity participation, and benefits commensurate with SVP-level executive roles at a well-funded, high-growth AI company backed by SAI Group
What draws people to is the opportunity to build something truly foundational.
We are at the beginning of a new era  — one where enterprise systems will no longer be static tools, but  dynamic collaborators  that learn, reason, and evolve alongside the people who use them. At , you’ll help build a platform that redefines how work happens in the  AGI era .
brings together vision, deep technology, and purpose . This is not about experimenting with AI features; it’s about turning the promise of  AGI  into  practical, auditable, and human-aligned systems that enterprises can trust and rely on at scale. The work here directly impacts productivity, efficiency, and decision-making in complex, real-world environments.
If you’re motivated by building systems that matter — systems that combine intelligence with responsibility — offers the chance to do that work at a deeper level, with real ownership and lasting impact.
Headquartered in Los Altos, CA. Backed by SAIGroup.
Learn more about : Website:   LinkedIn:  
Learn more about SAIGroup: Website:

Другое

End-to-end JazzX engineering function across the shared platform and domain application/solution layers, enabling reuse at scale while delivering measurable customer outcomes in production. Includes architecture, development, delivery, reliability, AI quality, security, infrastructure, operations and engineering org design and scaling.
Full-stack engineering organization across platform engineering, application and solution engineering, AI/ML, data and integrations, infrastructure, security, DevOps, and QA.
Distributed engineering organization across the US and India, with senior leadership in both. GTM organization is currently in the US, expected to grow globally. 
Own the engineering strategy across the JazzX platform and the solutions built on top of it. Define the next stage of architectural maturity—setting priorities across platform capabilities domain applications, and new deployment models so JazzX scales as a platform company, not a bespoke services business. Aligns engineering strategy tightly with business growth goals building toward a platform capable of supporting a $1B+ ARR trajectory.
Evolve JazzX's AI-native capabilities from functional to enterprise-grade and production-hardened. Build evaluation frameworks, benchmarks, regression coverage, and feedback loops. Strengthen explainability, auditability, governance, and human-in-the-loop controls based on real deployment needs. Establish consistent standards for reliability, observability, and failure handling as usage scales across customers and domains.
Make clear, durable decisions about what belongs in the shared platform versus solution layers, configuration/integration, or customer-specific scope. Systematically convert repeated patterns from live deployments into reusable services, frameworks, and tooling. Protect the platform from fragmentation while enabling speed.
Build strong mechanisms to convert customer deployments, delivery learnings, and workflow gaps into reusable platform improvements. Ensure JazzX learns from every deployment and systematically turns that learning into stronger, more repeatable platform assets.
Evolve current execution practices into a disciplined, high-throughput engineering system. Strengthen planning, design review, and delivery rhythms. Raise the bar on release quality, incident response, and observability. Make trade-offs explicit and data-driven across scope, timelines, reliability, and technical debt.
Turn current deployment experience into a repeatable, faster go-to-production engine. Reduce time-to-value for new customers and domains. Capture and productize deployment learnings into platform improvements that compound across every new vertical. The target: a new domain in production in roughly three months, with minimal architecture changes required.
Evolve the JazzX platform from internally usable to externally extensible and partner-ready. Mature APIs, integration patterns, configuration models, documentation, and developer experience so partners, portfolio teams, and advanced customers can extend the platform with decreasing reliance on core engineering.
Lead and scale the engineering organization—including engineering managers, architects, technical leads, and individual contributors across platform, AI/ML, data, infrastructure, and QA. Establish clear ownership, decision-making frameworks, operating cadence, and talent development across a distributed US-India environment.
Serve as the senior engineering counterpart to Product, GTM, Customer Delivery, and executive leadership. Align roadmap, release priorities, customer commitments, and long-term platform investments so JazzX can move quickly without losing rigor or compounding technical debt.
Has built or scaled engineering organizations for AI-native enterprise software—owning both a shared platform and the application/solution layers on top.
Navigates the inherent tension between platform investment, product development, and customer delivery without letting any dimension stall. Transitions teams from early-stage experimentation and speed to disciplined, repeatable systems for production at scale. Aligns engineering execution tightly with business growth goals (toward a $1B+ ARR trajectory).
Has experience scaling a live engineering organization from early-stage to production at scale—while also launching new capabilities, entering adjacent markets, or expanding into new domains. Comfortable operating in both modes at the same time.
Defines and evolves architectural boundaries across platform, application, Configuration/integration, and custom layers. Makes clear, durable decisions on what belongs in each layer. Converts repeated deployment patterns into reusable platform services, tooling, and frameworks.
Deep fluency in modern AI system design and real-world deployment challenges—including LLMs, retrieval systems, agents, orchestration, evaluation frameworks, and prompt/context engineering. Understands probabilistic system behaviour, guardrails, feedback loops, and quality measurement. Builds AI systems that power mission-critical workflows despite imperfect models and evolving capabilities. Bridges AI components with distributed systems, APIs, and enterprise-grade reliability expectations. Credible partner to Product and able to make strong engineering judgments in a fast-moving AI environment.
Translates strategy into clear architecture, delivery rhythms, and execution. Owns roadmap execution from design to stable production systems. Establishes strong SDLC practices, observability, release discipline, and operational rigor without creating unnecessary processes.
Designs platforms serving multiple constituencies: internal teams, enterprise customers, and partners. Understands cloud and AI infrastructure, inference cost dynamics, and scaling trade-offs. Makes principled decisions across performance, cost, and AI quality. Builds instrumentation and operating rhythms to continuously manage cost and efficiency at scale.
Deep understanding of enterprise identity, security, permissions, auditability, data lineage, and policy enforcement. Designs for reliability, recoverability, and compliance from the ground up. Comfortable operating in regulated domains where correctness, controls, and process fidelity are critical—including lending, insurance, healthcare, and legal. Treats trust, safety, and governance as first-class engineering requirements, not compliance afterthoughts.
Effective leading distributed engineering teams across the US and India. Drives alignment, execution quality, and talent development across geographies and time zones.
 Has recruited and developed strong engineering leaders and senior engineers. Establishes clear decision rights, ownership, and operating cadence. Builds an engineering culture with urgency, craftsmanship, accountability, and company-first thinking—without slowing innovation.
At the highest level, this leader will be measured on three things: building a world-class AI-native engineering organization, hardening JazzX into an enterprise-grade platform ready for hypergrowth, and enabling the company to scale repeatably across domains, customers, and partners. In the first 12–18 months, this leader will be expected to:
Clarify and consistently apply architectural boundaries across platform, solution, and configuration layers. Begin converting repeated deployment patterns into reusable platform capabilities—reducing rework and bespoke drift across every new customer and domain.
Raise AI quality, reliability, observability, and security to enterprise-grade standards. Improve deployment velocity so new customers and workflows reach production faster, with fewer surprises and less one-off engineering.
Demonstrate that JazzX can launch solutions in a new domain in roughly three months with minimal architecture changes. Partner- and portfolio-ready platform surfaces are real: APIs, integrations, and tooling enable extension with significantly less direct engineering involvement.
Replace early-stage execution habits with a disciplined, high-throughput delivery system—stronger planning rhythms, release quality, cross-functional alignment, and a culture that balances speed with craftsmanship.
Recruit and develop senior technical leaders across platforms, AI/ML, infrastructure, and solutions. Establish clear ownership and decision-making frameworks so the organization can sustain hypergrowth without losing quality or momentum.