brightwheel

• Design and deploy a lead scoring model using high-intent product, behavioral, and firmographic signals — working from data in Redshift, Salesforce, Gong, and Clay. • Build and maintain lead routing and distribution logic across inbound and outbound channels using LeanData and Salesforce, including guardrails, alerting, and monitoring. • Automate recurring analytical workflows — distribution checks, connect rate diagnostics, closed-loss tagging, resting period analysis — so they run without manual intervention. • Use AI tools (Claude, Gong transcript analysis, NLP pipelines) to extract signal from sales interactions at scale and surface actionable insights to Sales leadership. • Partner with Sales, Marketing, and RevOps to define ICP, improve lead quality, and translate analytical output into operational and strategic decisions. • Build and maintain the knowledge infrastructure (routing logic documentation, signal dictionaries, model documentation) so the team's work is institutional, not individual.

• Ship "virtual employee" workflows that do real work before humans engage: research, verification, prioritization, deduplication, and prep artifacts that cite evidence and flag unknowns. • Design the data foundations that let AI stitch together longitudinal operational signals across domains (customers, prospects, interactions, transcripts, product, ops, billing, support) into reliable workflows. Build evidence-first pipelines that produce structured outputs with provenance and uncertainty handling, and that store artifacts rather than overwriting truth. • Build a durable job execution system for agent workflows: retries, explicit budgets, idempotency, and monitoring. • Create shared abstractions for AI and data systems: tool interfaces, logging, cost tracking, evaluation harnesses, data contracts, SLAs, and reusable workflow components that increase trust in both data and AI outputs. • Partner with internal teams as customers. Define success metrics with them, design workflow delivery surfaces, and iterate based on adoption and impact. • Lead by example in AI-augmented engineering, using AI tools to increase velocity while maintaining architectural rigor.

• Build, scale and improve employee-facing processes that help teams thrive: You'll work on projects focused on performance management, annual reviews, employee engagement, career pathing and development, workforce planning, feedback and reviews, and compensation. • Mentor and develop the HRBP team: Serve as a thought partner and coach to other HRBPs; share frameworks, advise on complex ER situations, and actively raise the capability of the team around you. • Support talent development & career pathways: You'll work on processes like talent planning, performance calibrations, compensation to ensure we are growing and rewarding our best talent competitively. • Coach and develop managers: Proactively partner with your managers to maintain a high-performance culture, hold their teams accountable, and operate with inclusivity. • Be a voice for our employees: Advise and support managers and team members through a wide variety of complex employee relations situations; ensure that all voices and perspectives are heard. • Leverage AI to scale your impact: Use AI tools to accelerate your work across employee relations documentation, policy drafting, manager coaching prep, engagement survey analysis, and workforce planning; identify and build AI-enabled workflows that raise the bar for the broader People team.

• Lead the Sales Operations function for Brightwheel’s Expansion business — which covers our emerging product lines including curriculum, professional development, and financial products — managing a team of 2 to start • Partner cross-functionally with Expansion business owners, Sales leadership, PDE, and Finance to define priorities, align on strategy, and translate analytical output into operational decisions. • Contribute to strategy — not just execution. Help GTM leadership think through how the Expansion function should evolve: what to build, in what sequence, and with what resources. Bring a point of view on how to structure go-to-market motions when selling multiple products to the same customer. • Design and implement scalable processes and playbooks that support the full Expansion sales motion — from lead routing and scoring to rep workflow, handoff design, and post-sale coordination. • Design and ship lead scoring models and value-based routing frameworks using product signals, behavioral data, and firmographic inputs from Salesforce, Gong, and Clay. • Build AI-driven analytical workflows — automated closed-loss analysis, Gong transcript classification, distribution QA, account segmentation — that run without manual intervention. • Run the Expansion funnel analytics cadence: connect rate diagnostics, close rate analysis, ICP development, and rep performance benchmarking. • Present in WBRs, MBRs, and exec forums; represent the Expansion Revenue Operations function with clarity and confidence.

• Own campaign strategy across the prospect and customer lifecycle — seasonal programs, reengagement, upsell, and pipeline support • Develop campaign concepts, write or direct copy, and build the creative from brief to send • Design and maintain a structured testing agenda that produces documented learnings and drives real change • Partner with PMM to translate messaging frameworks into lifecycle campaigns, and close the loop so campaigns inform strategy • Work alongside the Lifecycle Marketing Manager to build a complementary, full-funnel lifecycle engine

• Design and deploy a lead scoring model using high-intent product, behavioral, and firmographic signals — working from data in Redshift, Salesforce, Gong, and Clay. • Build and maintain lead routing and distribution logic across inbound and outbound channels using LeanData and Salesforce, including guardrails, alerting, and monitoring. • Automate recurring analytical workflows — distribution checks, connect rate diagnostics, closed-loss tagging, resting period analysis — so they run without manual intervention. • Use AI tools (Claude, Gong transcript analysis, NLP pipelines) to extract signal from sales interactions at scale and surface actionable insights to Sales leadership. • Partner with Sales, Marketing, and RevOps to define ICP, improve lead quality, and translate analytical output into operational and strategic decisions. • Build and maintain the knowledge infrastructure (routing logic documentation, signal dictionaries, model documentation) so the team's work is institutional, not individual.

Role Description In this role, you’ll own AI-powered improvements in core brightwheel workflows end-to-end, from opportunity sizing to launch to iteration. You’ll ship experiences that make administrators and teachers faster and more effective, while creating shared patterns and infrastructure that enable the broader engineering team to build safely and consistently. - Design and build cross-cutting AI services (such as retrieval, context, evaluation, and guardrails) that power multiple product areas like classroom workflows, billing, and family communication. - Own the end-to-end product loop as a hybrid PM+Eng+Data builder: talk to customers and internal teams, define success metrics, design workflows and user experiences, shape data and evaluation plans, and ship iterative releases from prototype to reliable, scalable production. - Create shared abstractions and tooling for AI — including common prompt and tool patterns, logging and monitoring, and reusable components — so other engineers can build on a consistent foundation. - Shape our data and system architecture so AI can safely stitch together longitudinal signals across product, billing, support, and operations, and recommend what should happen next — not just report what happened. - Lead by example in AI-augmented engineering, using AI to multiply your own speed, mentoring L2/L3 engineers, and raising the bar for how we design, ship, and operate AI-powered features. Qualifications - 5+ years of professional software engineering experience, with clear ownership of medium-to-large production systems from problem statement and design doc through launch and iteration. - A proven track record of shipping AI-powered products to production, with concrete examples where LLMs meaningfully improved metrics like engagement, time saved, satisfaction, or retention. - Hands-on experience with large language models (LLMs) in real applications, including prompt and tool design, retrieval-style patterns (such as RAG), and evaluation and monitoring in production. - Strong computer science fundamentals (e.g., data structures, algorithms, and systems design) and a generalist mindset, comfortable moving between backend, data, and UX to get the job done. - Backend engineering skills in at least one modern web stack (such as Ruby on Rails, Python, Go, or Node), plus confidence with relational databases and larger datasets, from data modeling to performant queries and analytics. - Experience building modern web front-ends, ideally with React or a similar component-based framework. Requirements - Driven by outcomes. - AI-native. - A product-driving technical leader. - Full stack with a platform mindset. - Thoughtful about AI’s limits. - Security-minded. Nice-to-haves - Formal training in computer science (4-year CS degree or equivalent depth in core CS topics). - A portfolio of personal AI projects, open-source work, or writing that shows how you think about applied AI in real-world settings. - Background in vertical SaaS, ecommerce, or other operations-heavy domains. - Experience designing shared platforms or frameworks (for example, internal SDKs, evaluation services, or experimentation tooling) adopted by multiple teams. - A track record of raising the bar for quality and operations: writing secure, testable, maintainable code; automating and simplifying dev/test/ops workflows; writing and reviewing design docs; mentoring other engineers; and contributing to hiring through interviews and feedback. Technology - Backend: Ruby on Rails, Sidekiq - Data: PostgreSQL on Amazon RDS, Redis, and event and analytics pipelines - Frontend: React with TypeScript and Emotion - Mobile: Native iOS (Swift) and Android (Kotlin with Jetpack Compose) - Cloud & Infrastructure: Docker, Kubernetes on Amazon EKS, GitHub Actions and FluxCD for CI/CD, and AWS services such as S3, CloudFront, CloudWatch, and SNS - AI & Automation: AWS Bedrock and other hosted large language models, vector search, orchestration and agent frameworks, and modern AI coding tools like Cursor

• Compensation design & administration — build, test, and maintain compensation plan models (OTE, base/variable split, accelerators, SPIFs) that drive rep behavior and revenue growth • Quota & floor design — own quota-setting methodology and floor design across segments, roles, and geographies; run scenario modeling and sensitivity analysis; lead calibration exercises with Sales leadership. • Headcount planning & forecasting — maintain rolling headcount models by role/team and produce hiring models tied to annual planning targets. • Annual Planning support — drive the people and comp assumptions for annual planning; translate targets into quota, ramp, and comp implications and produce what-if analyses. • Monthly performance & forecasting cadence (MPE) — own month-end reporting (attainment, forecast vs. actuals) and recommend corrective actions. • Promotions & special programs — assess promotion impacts on pay and quotas; design SPIFs/short-term incentives and measure program effectiveness. • Comp reporting & governance — own recurring comp reporting, ad-hoc analyses, and audit controls; document runbooks and change-management processes. • Systems & automation — partner with Systems/IT to maintain Salesforce and comp tooling, automate repetitive tasks, and improve data flows. • AI-enabled productivity — build agentic workflows and automations that compress cycle times on modeling, reporting, and analysis; set the bar for what "AI-native" operating looks like on the team. • Cross-functional partnership — translate technical models into clear recommendations and build trusted relationships with Revenue leaders, Finance, People/HR, and Recruiting. • Executive communication – Present directly with the CEO and executive team.

• Compensation design & administration — build, test, and maintain compensation plan models (OTE, base/variable split, accelerators, SPIFs) that drive rep behavior and revenue growth • Quota & floor design — own quota-setting methodology and floor design across segments, roles, and geographies; run scenario modeling and sensitivity analysis; lead calibration exercises with Sales leadership. • Headcount planning & forecasting — maintain rolling headcount models by role/team and produce hiring models tied to annual planning targets. • Annual Planning support — drive the people and comp assumptions for annual planning; translate targets into quota, ramp, and comp implications and produce what-if analyses. • Monthly performance & forecasting cadence (MPE) — own month-end reporting (attainment, forecast vs. actuals) and recommend corrective actions. • Promotions & special programs — assess promotion impacts on pay and quotas; design SPIFs/short-term incentives and measure program effectiveness. • Comp reporting & governance — own recurring comp reporting, ad-hoc analyses, and audit controls; document runbooks and change-management processes. • Systems & automation — partner with Systems/IT to maintain Salesforce and comp tooling, automate repetitive tasks, and improve data flows. • AI-enabled productivity — build agentic workflows and automations that compress cycle times on modeling, reporting, and analysis; set the bar for what "AI-native" operating looks like on the team. • Cross-functional partnership — translate technical models into clear recommendations and build trusted relationships with Revenue leaders, Finance, People/HR, and Recruiting. • Executive communication – Present directly with the CEO and executive team.

• Manage and optimize calendars for multiple executives, ensuring effective prioritization and minimal conflicts • Coordinate meetings across internal teams, external partners, and time zones • Support inbox management, including organizing, responding, and flagging key items • Handle expense reporting, reimbursements, and tracking to ensure timely and accurate submissions • Arrange travel, accommodations, and logistics for executives • Support planning and execution of team events, all-hands, and offsites • Coordinate team culture initiatives such as celebrations, milestones, and recognition (e.g., Kudoboards) • Provide ad-hoc administrative support including document preparation, research, and process coordination