Senior Software Engineer

Senior Software Engineer, Platform Whisker is redefining what it means to live with cats—designing intelligent systems that remove friction, elevate the everyday, and celebrate the quiet brilliance of feline companionship. Today, Litter-Robot leads the category. Tomorrow, an entire ecosystem that expands what's possible for cats and the people who love them. We believe the future is feline. And we're imagining that future today. The Senior Software Engineer, Platform builds and operates the shared services, pipelines, and infrastructure that Whisker's product engineering teams depend on. This is a hands-on senior individual contributor role on a newly formed Platform team: you will design and operate backend services at scale, lead migrations of production systems that serve a live fleet of connected devices, and build the ingestion path that moves high-volume IoT telemetry into Whisker's analytics platform. You will own the reliability of what you build, including on-call, and you will raise the technical bar of the engineers around you through design review, mentorship, and the standards you set in code. We build with AI agents here, deliberately and with guardrails, and we are extending that capability into the platform itself. You will be expected to work fluently with agentic tooling — and to hold the line that the engineer who opens the pull request is accountable for it, whether or not a model wrote the first draft. This role suits an engineer already operating at the top of Senior who wants a wider platform charter than a single product team can offer. The Senior Software Engineer (Platform) at Whisker is responsible for designing, building, and operating the shared backend services, infrastructure, and high-volume IoT telemetry pipelines that support the company's product engineering teams. This senior-level individual contributor role requires hands-on expertise in cloud-native AWS environments and agentic development workflows, with a core focus on system reliability, platform migration, and technical leadership. This list of duties and responsibilities is not all-inclusive and may be expanded to include other duties and responsibilities as deemed necessary. Designs, builds, and operates shared backend services and platform capabilities that other engineering teams depend on Owns service reliability end to end including participation in an on-call rotation, incident response, and the operational health of the systems you build Establishes and improves the paved road: service templates, deployment pipelines, observability defaults, and infrastructure-as-code that make the right thing the easy thing for other teams Designs for scalability, availability, and operational cost, and makes those trade-offs explicit rather than implicit Extends the platform's AI capability including inference paths, agent infrastructure, and the evaluation and guardrail work that makes agent output trustworthy in production Leads migrations of production systems serving live connected devices, sequencing the work so that customers are not disrupted and rollback remains possible Models the failure modes that matter for connected hardware like a device that is offline, a firmware version that cannot be updated, a network that drops mid-command — and designs for them ahead of time rather than discovering them in QE Retires legacy paths deliberately, including the dual-run, backfill, and verification work that makes a cutover safe Builds and scales ingestion pipelines for high-volume device telemetry, routing it reliably into Whisker's data and analytics platform Designs data contracts and schemas that survive change, and partners with Data Engineering, Data Science, and Analytics so the data arriving is the data they can actually use Instruments the pipeline itself — freshness, completeness, cost — so problems are detected upstream of the dashboard that depends on them Owns work that crosses systems and team boundaries, anticipating integration problems early and driving them to resolution Surfaces risk early and proposes alternatives, rather than escalating a problem without a path forward Holds a high quality bar in code review and closes out systemic defects rather than their latest instance. Mentors engineers deliberately and raises the capability of the team around them Represents the team's technical position credibly to Product, TPM, and partner engineering teams, translating trade-offs into terms non-engineers can decide against Champions best practices in testing, code quality, security, and observability, and helps establish patterns other engineers build against Works agentically by default by decomposing work so an agent can be steered and reviewed at each step, curating the context and skill files that make agent output good, and treating a generated diff as a draft to be understood rather than output to be forwarded Improves how the team builds with AI: better skills, sharper review gates, and honest assessment of where agents help and where they do not Will perform additional responsibilities when required Our Tech Stack: Cloud-native, largely serverless infrastructure on AWS Cloudflare, newly being introduced alongside AWS for edge and network-layer services REST APIs via AWS API Gateway, and GraphQL APIs DynamoDB and other serverless data stores AWS IoT Core and streaming/event infrastructure for a large connected-device fleet Databricks as the analytics and lakehouse platform Amazon Bedrock and a growing set of AI and agent capabilities across the platform Modern TypeScript and Python codebases Infrastructure as code, CI/CD, and centralized observability tooling Agentic development as the default workflow — curated skill libraries, project memory files, and agent-assisted pre-review, with a human gate at every step High-Level 2-Year Scope of Product Development: Platform: Help stand up and mature a shared platform layer — services, tooling, and conventions — that product-facing teams build on. Migration: Move core device and services workloads onto the next-generation backend platform without customer-visible disruption. Data: Build the telemetry ingestion path from device to analytics platform, at fleet scale and with reliability treated as a product requirement. Reliability: Establish meaningful SLOs, on-call practice, and operational maturity for platform services. Team Leadership: Define and drive technical direction for the broader software engineering practice. Requirements: What You'll Bring: BS in Computer Science, Computer Engineering, or equivalent experience 7+ years of backend development with 5+ years architecting systems in AWS Strong proficiency in Python and/or TypeScript, and in SQL 6+ years of experience in backend development Hands-on experience with core AWS services relevant to this role, such as Lambda, API Gateway, DynamoDB, Kinesis, ECS, and IAM. Current, hands-on practice with agentic development tooling, and the judgment to go with it: working an agent from structured context rather than one-line prompts, breaking work down so each step can be reviewed, correcting an approach before it becomes two hundred lines, and running an agent-assisted review pass before a human sees the pull request. We care about how you work, not which vendor's tool you have used. Accountability for AI-assisted output. You can explain every line you submit and defend it in review; "the model wrote it" is not an answer you would give. Experience building LLM- or agent-backed capability into a production system — inference integration, tool and function calling, retrieval, evaluation, or guardrails — or clear evidence you can pick it up quickly. Demonstrated experience building and scaling data or event pipelines in production. Experience with CI/CD pipelines, infrastructure as code, and containerized workloads. Experience with REST and/or GraphQL API design in distributed systems. Experience carrying production on-call responsibility for systems you built. Track record of leading a significant migration or platform initiative to completion. Solid data modeling and systems design fundamentals, including designing for observability and cost. Clear written and verbal communication, including the ability to explain technical trade-offs to non-technical partners. Strong problem-solving, organizational, Whisker