Engineering Jobs in Seattle, WA (Now Hiring) — 3,480 open — Page 9

About the Role 

We are seeking a Senior Director of Engineering to lead the architecture, software and application management, integrations, and reliability of the platforms that power how Keystone operates. As the firm expands its business lines and geographic reach — and grows the organization to meet our clients’ needs— the ability to scale the systems that support client delivery, operations, and corporate workflows is central to Keystone's ability to grow. 

This role sits at the intersection of IT, Product, and Engineering, focused on evolving Keystone's technology stack into a coherent, resilient operating environment. Two priorities shape the near-term charter. First, investing thoughtfully in architecture for scale and resilience — hardening the integrations, data flows, and platform foundations the firm depends on, so the environment’s design incorporates growth as a leading tenet. Second, investing deliberately in AI as a source of leverage for consultants and operators — automating manual effort, accelerating workflows, and scaling the firm's collective capability. 

The technology environment under spans a customer relationship management platform, a cloud financials and ERP platform, multiple frontier generative AI providers, hyperscaler cloud infrastructure, a cloud data warehouse, an enterprise productivity and collaboration suite, an enterprise content management platform, and a broader portfolio of third-party SaaS applications supporting client delivery, resource planning, knowledge management, HR, Finance and other corporate workflows. 

This role partners with the head of VP of Technology to set the technical roadmap, drive DevOps and reliability practices, and ensure engineering delivers measurable business outcomes. It works closely with Product Management, Security, Cloud and AI leaders, and the business function leaders whose workflows depend on these systems every day. 

You will take well-defined and ambiguous technical problems, shape them into architectural direction, engineering execution, and operational discipline that hold up at scale, and drive outcomes through a mix of leadership, hands-on judgment, vendor management, and stakeholder partnership. 

This is a hybrid role with a minimum in office requirement of 3 days per week.

 

What You'll Do 

Engineering Ownership & Execution 

• Own the engineering charter for Keystone's platform portfolio end-to-end, from architectural direction through delivery, DevOps, and iteration. 
• Translate IT/Product and business priorities into clear technical roadmaps, system designs, and prioritized engineering backlogs. 
• Set the standards for how systems are designed, deployed, secured, and operated across the estate, so quality does not depend on which team happens to be building. 
• Contribute directly to critical decisions and hands-on judgment on prototypes, technical spikes, and complex integration work when it accelerates outcomes. 
• Lead a development team on execution of product and platform development efforts, establish dev ops practices and telemetry to monitor performance and identify issues proactively.  

Architecture, Scale & Resilience 

• Own the multi-year technical architecture for Keystone's platform portfolio — the SaaS ecosystem, cloud infrastructure, data platform, integration fabric, and internally-built products — and evolve it as the firm scales into new geographies, practices, and consultant volumes. 
• Establish service level targets — availability, latency, recovery, data integrity — that reflect the criticality of each system to consultant delivery, client engagement, and corporate operations. 
• Drive a durable investment program in resilience: redundancy, failover, backup and recovery, disaster-recovery drills, capacity planning, and the retirement of brittle or single-threaded components before they fail under load. 
• Partner with Security and Compliance on architecture decisions that touch client data, cross-border data flows, identity, and access — making the secure path the default path. 

AI Strategy & Enablement 

• Invest thoughtfully — favouring durable capability, measurable leverage, and responsible use over adoption for its own sake. Frame AI investment in terms of specific outcomes: hours returned to consultants, quality lifted, time-to-answer reduced, manual tasks eliminated. 
• Build and operate the internal platform that makes AI secure, cost-aware, and accessible — model access, prompt and context management, evaluation harnesses, guardrails, observability, and the connective tissue between AI and the firm's systems of record. 
• Establish patterns for embedding AI into consultant-facing and operational workflows so that adoption is fast, quality is measurable, and human review sits where it belongs. 
• Participate as a member of the AI Governance Committee for direction, policy and execution of the governance model for AI use — data handling, model choice, client-work considerations, and the internal policies that guide when and how AI is applied. 

Integrations & DevOps 

• Own the integration fabric that connects Keystone's SaaS platforms, internally-built products, data warehouse, and AI capabilities into a coherent operating environment — so that a change of a client, project, or employee flows once and is reflected everywhere it needs to be. 
• Establish integration patterns and standards (event-driven, API-first, idempotent, observable) that reduce point-to-point coupling and make new integrations cheaper and safer to build over time. 
• Own the end-to-end DevOps lifecycle across engineering teams — source control, CI/CD, environment management, infrastructure-as-code, release management, and post-deployment monitoring — with the aim that changes ship frequently, safely, and with fast rollback when needed. 
• Set uptime targets and integration reliability SLOs; instrument systems to make performance measurable and issues detectable early. 
• Curate the middleware, iPaaS, ETL/ELT, and event-streaming tooling used across the firm; make deliberate build-vs-buy decisions and retire redundant tools. 

Issue Management & Support 

• Own the issue management and resolution pipeline end-to-end — from intake, through triage, engineering resolution, and communication back to affected users — with clear ownership, SLAs, and reporting to firm leadership on health and trends. 
• Build a mature incident management practice: on-call rotations, severity definitions, response protocols, communication standards, postmortems, and a feedback loop that reduces repeat incidents over time. 
• Partner with the leader of the IT Admin organization on the design and operation of the technical support model that consultants and operators experience day-to-day — tiered support, escalation paths, self-service where appropriate, and the tight coupling between support signal and engineering roadmap. 
• Establish and report on operational metrics — availability, mean-time-to-detect, mean-time-to-resolve, deployment frequency, change failure rate, integration SLOs, backlog age — that make the health of the estate visible and drive continuous improvement. 

Stakeholder & Business Partnership 

• Partner with Product Management to translate product strategy into technical roadmap, and hold a joint view of priorities, tradeoffs, and delivery risk. 
• Partner with consulting practice leaders, finance, HR, and operations leaders — so engineering decisions reflect how the business actually runs, and so business leaders understand the technical constraints and choices ahead of them. 
• Represent engineering outcomes to firm leadership: system health, integration risk, AI leverage delivered, incident trends, and the return on architecture investment. 
• Own vendor relationships for the platforms and infrastructure the team operates — driving accountability on roadmap commitments, uptime, integration quality, and cost. 

Team Leadership & Development 

• Build, lead, and develop the engineering organization — hiring, leveling, coaching, performance, and succession — across platform engineering, integrations, DevOps/SRE, and support functions. 
• Shape the operating model that lets a growing engineering team stay coherent as it scales: team topology, on-call practice, engineering rituals, technical decision-making, and the balance between central platform teams and product-aligned squads. 
• Set the bar for engineering craft, code quality, code review, testing discipline, and technical documentation, and hold the team to it. 
• Manage the mix of full-time engineers, contract engineers, offshore partners, and vendor implementation teams to deliver against the roadmap. 
• Own the engineering budget and forecast — cloud spend, SaaS spend, model spend, tooling, and people — and defend it credibly to firm leadership. 

Systems Thinking & Continuous Improvement 

• Design solutions that work across systems and reduce fragmentation between consultant delivery, client engagement, and back-office data. 
• Identify opportunities to introduce automation and AI to improve efficiency and reduce manual effort across the estate. 
• Improve systems based on usage patterns, incident trends, feedback, and evolving needs — including new geographic, regulatory, and practice-specific requirements as the firm expands. 

What You'll Bring 

• 10+ years of engineering experience, including 6+ years leading engineering organizations in environments with a broad SaaS estate, meaningful cloud footprint, and mission-critical integrations. 
• Track record of investing in architecture for scale and resilience — measurable improvements in availability, recovery, incident volume, or the ability to absorb growth without proportional operational cost. 
• Deep experience with integration architecture and the operational discipline required to run integrations well at scale — event-driven patterns, API design, data contracts, error handling, and observability. 
• Strong grounding in modern DevOps practice — CI/CD, infrastructure-as-code, observability, incident response, SRE principles — and demonstrated ability to raise the bar on these practices in a real organization. 
• Practical, current experience applying generative AI to real workflows, and a considered point of view on where AI creates durable leverage versus where it does not. 
• Hands-on comfort with hyperscaler cloud infrastructure and modern data platforms; ability to make credible architecture judgments without needing to be the deepest expert in any single system. 
• Track record building and running high-performing engineering support and issue-management functions that users trust. 
• Partnership-oriented leadership style — comfort operating alongside Product, Security, Data, and business leaders as peers, and credibility to represent engineering to firm leadership. 
• Strong written and verbal communication, including the ability to explain technical tradeoffs to non-technical stakeholders and to write clearly for decision-makers. 

Nice to Have 

• Experience in consulting, professional services, or another people-intensive services business where consultant leverage and utilization matter. 
• Experience operating engineering teams across multiple geographies and time zones, including EU data-residency considerations. 
• Experience building internal AI platforms — model access layers, evaluation frameworks, prompt and context management, cost controls — and running agentic AI systems in production. 
• Experience leading through an ERP, CRM, or PSA replacement, or comparable large-platform migration, without disrupting operations. 
• Experience owning a cloud FinOps discipline — visibility, budgets, unit economics, and cost accountability for cloud, SaaS, and model spend. 
• Experience partnering with Security and Compliance to achieve or maintain SOC 2, ISO 27001, or comparable certifications.