Senior Manager, Engineering (Nova)

Iterable•Chicago, GA

7d•Remote

About The Position

We are looking for a Senior Engineering Manager to lead the engineering groups responsible for building agentic experiences and integrating AI-powered capabilities into the core Iterable application. This organization owns the critical application-facing development that turns emerging AI capabilities into reliable, highly scalable, and usable product features. In this role, you will provide strategic direction and leadership to a growing organization of frontend, backend, and applied engineers working on conversational workflows, orchestration layers, and AI-enabled product surfaces. You will balance organizational leadership with high-level technical vision, helping teams deliver complex, high-impact features while defining roadmaps, navigating ambiguity, and driving architectural standards in a fast-moving product area. This role sits within the broader Nova initiative and plays a strategic part in shaping the future of how intelligent experiences appear across the Iterable platform. One of our core values is a growth mindset and Iterable is a company where everyone can grow. If this is a role that excites you, please do apply as we value applicants for the skills they bring beyond a job description.

Requirements

At least 8+ years of hands-on software development experience.
At least 5+ years of experience managing, scaling, and leading software engineering teams.
Strong background in application or platform engineering, with a proven track record of scaling systems in a SaaS environment.
Experience leading teams that integrate complex AI or ML-powered capabilities into production systems.
Demonstrated expertise in building alignment and operating seamlessly at the intersection of product, platform, and data science teams.
Exceptional technical judgment across system design, APIs, distributed systems, and developer workflows, with the ability to guide teams through complex technical decisions.
Experience overseeing engineering work across modern backend and frontend stacks.
Ability to thrive in ambiguity, define strategic direction, make pragmatic trade-offs, and drive execution across multiple concurrent initiatives.
Excellent executive communication skills and the ability to articulate how technical work maps to overarching business and product goals.

Nice To Haves

Experience managing engineering managers or leading multiple autonomous squads.
Experience leading teams building agentic, LLM-powered, or generative AI product experiences.
Familiarity with agent frameworks such as Mastra, LangChain, or similar orchestration tools.
Prior leadership work on decisioning engines, rules engines, or real-time personalization systems at scale.
Experience collaborating closely with Data Science and ML teams on complex production integrations and model deployment pipelines.
Background in marketing technology or customer engagement platforms.
Experience successfully scaling engineering teams and systems in a remote-first or distributed environment.

Responsibilities

Lead and scale multiple engineering teams (or a large, multi-disciplinary pod) building agentic and AI-enabled product experiences.
Act as a strategic partner to Product, Design, and Data Science leadership to define the technical roadmap, prioritize initiatives, and translate AI capabilities into scalable, user-facing experiences.
Drive the overarching technical architecture and design of agent workflows, orchestration logic, and application integrations.
Establish the standards to ensure AI-powered features are reliable, observable, secure, and ready for enterprise-scale production use.
Spearhead execution across complex, cross-functional initiatives, balancing short-term product delivery with sustainable, long-term technical direction.
Champion and elevate strong engineering practices around code quality, system resilience, testing, and iterative delivery across the broader engineering organization.
Coach, mentor, and sponsor senior engineers, technical leads, and potentially other engineering managers, actively supporting their career growth and ensuring a healthy, inclusive team culture.
Collaborate strategically with principal engineers, data teams, and platform architecture groups to align on system interfaces, resolve organizational dependencies, and achieve shared business goals.
Drive hiring, headcount planning, and onboarding strategies as the AI engineering organization scales.