In Tandem

• Getting to know teammates, technology, and tactics. Your first day, you'll pair with your manager and a colleague to set up your local environment and ship a bug fix — using our agent workflows end to end. The following 29 days involve connecting with engineers across the professional experience and Reporting to understand how we prioritize, plan, build, and deliver value on OurFamilyWizard. You'll get immersed in daily and weekly agile rituals, the API guild, and our internal skills and plugins ecosystem. By the end of your first month, you'll be running your own spec-to-ship cycles inside Pro Core's domain — the professional user experience and Reporting. • Try, learn, ship. By day 60, you're operating our SDLC from planning through production release — authoring specs, orchestrating multi-file agent work, and reviewing outcomes rather than lines. You'll have a broad understanding of our backend architecture and deeper expertise in the services Pro Core owns and the APIs powering both the professional user experience on OurFamilyWizard and our Reporting product. You'll ship to production several times a day and start contributing skills and plugins that the rest of engineering can reuse. • Solidifying the foundation. Beyond month two, you grow into an autonomous operator — architecting solutions to complex problems, defining specs sharp enough that agents can execute them, and calibrating when a problem needs human hands vs. agent iteration. You'll partner with cross-functional teammates and leadership to shape execution plans for new features. We'll start conversations about long-term team alignment between days 30–60 and target a 3–4 month rotation. • Accelerate growth. With foundational understanding gained, you'll inform platform-level change and find your team home. Complex product problems, scale and modernization challenges, and the frontier of AI-integrated product experiences will establish you as a subject-matter expert and expand your ownership.

• Build & Own a Modern Revenue Operating System • Serve as the strategic owner of HubSpot CRM and related GTM systems, designing scalable workflows, lifecycle stages, and pipeline reporting that support Sales and Marketing. • Eliminate manual processes through automation, tooling, and systems optimization. • Improve how leads flow, opportunities are managed, and customer data is used across the organization. • Ensure our HubSpot architecture evolves alongside the business to support long-term growth. • Drive AI-Enabled Efficiency & Productivity • Identify and implement AI-powered workflows that reduce manual work, partnering closely with GTM Engineering/Data teams. • Increase team effectiveness by improving how work is prioritized, executed, and measured across the revenue organization. • Continuously evaluate emerging AI GTM capabilities and bring new sales/GTM tools to the business. • Build Revenue Intelligence & Visibility • Build reporting and insights that give leaders actionable visibility into pipeline health, forecasting, conversion trends, and business performance. • Improve data quality, governance, and reliability across systems. • Translate data into strategic recommendations that help leadership spot trends, risks, and opportunities earlier. • Improve Cross-Functional GTM Execution • Partner closely with Sales, Marketing, and Leadership to improve alignment across the customer lifecycle. • Support onboarding, enablement, documentation, and process adoption where needed.

• Ship the models that power personalized in-app experiences — predicting what each member is likely to want next based on real-time behavior, family context, and engagement history. • Detect meaningful patterns in product usage data — communication, scheduling, and activity signals — and build the models that turn those patterns into in-app suggestions, alerts, and guidance for families. • Help replace fixed-placement UI logic with algorithmic decisioning that adapts every time someone opens the app. • Build the churn, retention, and activation models that help Product understand which behaviors predict long-term value and which interventions are worth shipping. • Develop predictive segmentation, propensity, and uplift models, refreshed continuously through automated pipelines so the rest of the business is always acting on current signal. • Partner with Finance on cohort-level subscriber and revenue forecasting, LTV by acquisition source, and sensitivity analysis on the assumptions that matter most. • Build pricing, promo, and refund-risk models that quantify the financial impact of monetization decisions before we ship them. • Train, deploy, and monitor models in Databricks and AWS, using Claude Code as your primary engineering interface. • When agentic delivery makes sense, wrap models in managed agents that surface predictions into the workflows stakeholders already use. • Move the team from "what happened" to "what would happen if" — uplift modeling, geo-tests, and A/B analysis grounded in proper causal framing.

• Run and optimize our self-hosted inference stack • Run the inference serving layer on our own GPU hardware: choose and tune the serving stack (vLLM, SGLang, TensorRT-LLM) for high throughput and low latency. • Optimize aggressively: tensor parallelism, quantization (FP8, AWQ, GPTQ), KV-cache and prefix caching, continuous batching, speculative decoding, concurrency tuning. • Serve multiple models and features off shared hardware: multi-LoRA, routing, and request scheduling that balances internal workloads against latency-sensitive product traffic. • Keep our AI fast, efficient, and observable • Make our AI workloads efficient: improve latency, throughput, and GPU utilization so we get the most out of what we run. • Build the visibility: instrument performance and usage across our AI surfaces so there's clear data on how everything is running. • Surface the technical tradeoffs (performance, latency, efficiency) so the people making the calls have what they need to make them. • Build AI features and proactive agents • Ship the in-app agent layer that helps families coordinate: proactive nudges, smart suggestions, agents that summarize, draft, schedule, and act for busy parents. • Build the substrate underneath: tools, memory, orchestration, guardrails, and evaluation harnesses, integrated cleanly with production APIs alongside our architecture team. • Work in nimble pairs with feature owners, standing up whatever's needed to test an idea, including a vibe-coded UI when that's the fastest path to a real customer. Ship rough, learn fast, harden what works.

• Run and optimize our self-hosted inference stack • Run the inference serving layer on our own GPU hardware: choose and tune the serving stack (vLLM, SGLang, TensorRT-LLM) for high throughput and low latency. • Optimize aggressively: tensor parallelism, quantization (FP8, AWQ, GPTQ), KV-cache and prefix caching, continuous batching, speculative decoding, concurrency tuning. • Serve multiple models and features off shared hardware: multi-LoRA, routing, and request scheduling that balances internal workloads against latency-sensitive product traffic. • Make our AI workloads efficient: improve latency, throughput, and GPU utilization so we get the most out of what we run. • Build the visibility: instrument performance and usage across our AI surfaces so there's clear data on how everything is running. • Surface the technical tradeoffs (performance, latency, efficiency) so the people making the calls have what they need to make them. • Ship the in-app agent layer that helps families coordinate: proactive nudges, smart suggestions, agents that summarize, draft, schedule, and act for busy parents. • Build the substrate underneath: tools, memory, orchestration, guardrails, and evaluation harnesses, integrated cleanly with production APIs alongside our architecture team. • Work in nimble pairs with feature owners, standing up whatever's needed to test an idea, including a vibe-coded UI when that's the fastest path to a real customer. Ship rough, learn fast, harden what works.

• Ship the models that power personalized in-app experiences — predicting what each member is likely to want next based on real-time behavior, family context, and engagement history. • Detect meaningful patterns in product usage data — communication, scheduling, and activity signals — and build the models that turn those patterns into in-app suggestions, alerts, and guidance for families. • Help replace fixed-placement UI logic with algorithmic decisioning that adapts every time someone opens the app. • Build the churn, retention, and activation models that help Product understand which behaviors predict long-term value and which interventions are worth shipping. • Develop predictive segmentation, propensity, and uplift models, refreshed continuously through automated pipelines so the rest of the business is always acting on current signal. • Partner with Finance on cohort-level subscriber and revenue forecasting, LTV by acquisition source, and sensitivity analysis on the assumptions that matter most. • Build pricing, promo, and refund-risk models that quantify the financial impact of monetization decisions before we ship them. • Train, deploy, and monitor models in Databricks and AWS, using Claude Code as your primary engineering interface. • When agentic delivery makes sense, wrap models in managed agents that surface predictions into the workflows stakeholders already use. • Move the team from "what happened" to "what would happen if" — uplift modeling, geo-tests, and A/B analysis grounded in proper causal framing.

• Lead operational readiness for the Home Hub launch, ensuring critical milestones, dependencies, and decisions stay on track • Drive alignment across Product, Engineering, Marketing, Finance, Customer Support, and external partners to execute a successful launch • Identify risks before they become issues and proactively drive resolution • Establish the operating rhythms, reporting, and accountability needed to keep launch execution moving forward • Provide leadership with clear visibility into launch readiness and operational performance • Ensure fulfillment, shipping, warranty, returns, and replacement processes are launch-ready and scalable • Create operational workflows that enable a high-quality customer experience from preorder through post-purchase support • Build strong partnerships with OEMs, fulfillment providers, logistics partners, and service vendors • Coordinate launch support readiness, customer communications, and escalation processes • Support the foundation for future international fulfillment and expansion • Partner with leadership on inventory planning, demand forecasting, purchasing, and replenishment decisions • Help balance customer demand, operational readiness, and business objectives as launch approaches • Establish clear processes for managing inventory health, fulfillment performance, and operational decision-making • Support launch-related commercial decisions that impact customer experience and business performance • Build dashboards and reporting that provide actionable insight into launch readiness and ongoing operations • Track key metrics across revenue, margin, inventory, fulfillment performance, warranty activity, and customer satisfaction • Create transparency around operational performance and areas requiring attention • Lead post-launch reviews and identify opportunities for continuous improvement

• Build and own our web analytics and tag management infrastructure. Implement Segment events, conversion pixels, and ad partner tags, and maintain the GTM foundation to add tracking and measurement without traditional engineering dependencies. • Build and ship landing pages and campaign assets—develop and deploy pages that support paid and organic campaigns, and build the component systems that make future work faster. • Drive CRO and experimentation—in partnership with our Director of Growth Marketing, set up and run A/B tests across our properties to improve conversion rates, and partner with Marketing to turn results into better experiences. • Maintain the technical health of our web properties—own technical SEO, site performance, structured data, and Core Web Vitals across all three brands so our properties are always well-positioned to perform. • Evolve our CMS and publishing infrastructure—own the CMS platforms across our three brands and build the infrastructure that makes Marketing genuinely self-sufficient on the web: component libraries, templates, and publishing workflows that enable the team to build, ship, and iterate without an engineering ticket. This means evaluating current stacks, identifying gaps, and making the case for investment when the platform is holding us back. • Shape the platform roadmap—bring a technical point of view to how we invest in our web properties over time, including platform modernization and the tools that will help Marketing move even faster in the future. • Own ad operations across all properties—serve as the reliable, responsive point of contact for ad partner requests, including ads.txt, script tags, Prebid config, and GAM surface management. Ad revenue depends on this working well, and you'll make sure it does.

• Elevate the visual expression of In Tandem across our portfolio of consumer brands • Own how they show up in the world across websites, paid media, app store listings, emails, and more • Collaborate closely with Growth, Product, and Marketing Leadership to ensure alignment in the journey to elevate our brands while maintaining consistency with our product experience • Mature and strengthen visual systems that can scale to a variety of channel executions • Collaborate in strategic brand strategy conversations to future-proof positions of our brands • Own website and landing page design strategy and execution • Develop high-performing page media creative (Meta, Google, TikTok, and emerging platforms) in both still and static formats • Partner with Growth Marketing to iterate and optimize creative based on performance data and audience insights • Lead creative for app store listings, visual positioning, and conversion optimization • Design for email and lifecycle marketing campaigns • Provide creative direction and oversight for video production (CTV ads, short-form video, podcast reads, motion graphics) • Increase brand affinity and trust through thoughtful, high-quality design • Raise the standard of creative excellence across the organization

• At In Tandem, we build technology that helps families manage everyday routines and navigate life’s biggest transitions. • If you want your work to make a real difference in the daily lives of parents and kids, In Tandem is the place where your impact will truly matter. • As a Senior Backend Engineer (Java), you'll join us in a unique rotational capacity that offers broad platform exposure and accelerated career growth. • In this role, you'll directly contribute to features that make everyday life a little bit easier for families. • Working as part of product teams, you'll collaborate with product managers, designers, QA analysts, automation engineers, and other web and mobile engineers to solve meaningful problems for parents, children, and practitioners across our platforms. • You'll be building robust, scalable backend services and APIs that power our family coordination platforms, working with modern technologies including AI-powered features that directly impact millions of families.