• Build and evolve web applications and dashboards (results exploration, reporting, operational tools). • Improve and maintain existing platforms: refactors, performance, UX improvements, and reliability work. • Design and implement APIs + data models that make data easy to query, audit, and reuse. • Create critical automation: scripts, tooling, and reproducible environments that reduce manual work. • Integrate with Python-first pipelines and modelling workflows (ETLs, orchestration tools like Snakemake, Apache Airflow or similar). • Own quality via CI/CD, pragmatic testing, and stable deployments. • Communicate clearly in a remote-first team: async docs, high-signal PRs, and thoughtful reviews.

• Influence the technical direction for infrastructure and platform capabilities that support our rapidly growing AI product suite. • Architect and evolve our cloud infrastructure (primarily on AWS) across container orchestration (Kubernetes, Elastic Container Service), serverless (e.g., Lambda), virtual machines (e.g., EC2), and data stores to support current and future products. • Work closely with Platform leadership, product engineering, data, and ML teams to design systems that are robust, observable, and compliant in a healthcare environment. • Define and drive infrastructure strategy for the Platform org—partnering with engineering leadership to align roadmaps, set standards, and sequence work for maximum business impact. • Secure networking, identity, and access patterns across environments. • Improve reliability and operational excellence by defining SLOs, SLIs, and error budgets for core platform services. • Leading and participating in blameless post-incident reviews and translating learnings into systemic improvements. • Own observability and monitoring strategy across logging, metrics, and tracing, ensuring we can detect, debug, and prevent issues efficiently. • Mentor and level up engineers across Platform and product teams—reviewing design docs, guiding architecture decisions, and modeling high standards for reliability, security, and maintainability. • Partner with security and compliance stakeholders to ensure our infrastructure and operational practices meet HIPAA and other healthcare requirements. • Advocate for and implement developer experience improvements, such as better CI/CD workflows, faster feedback loops, and tooling that reduces cognitive load for product teams.

• Handle complex technical design discussions across various stakeholders • Design, implementation, and maintenance of resilient, high-performance, and scalable software solutions optimized for the macOS platform • Drive engineering initiatives • Debug complex problems and analyze stack traces from crash dumps • Collaborate with product management, cross-functional teams, and external groups to define and deliver required solutions • Implement and improve processes around DevOps, Agile, and CI/CD

• Design and implement AI workflows on top of existing data pipelines (product feedback extraction, customer update generation, onboarding plans, win/loss summaries, CRM enrichment) • Extend and refine the current TypeScript-based agent: tooling, tool schemas, routing logic, error handling, and observability • Improve transcript and account matching across Zoom, Granola, and Salesforce using entity resolution, heuristics, and/or LLM-assisted matching • Integrate new data sources (Slack, Zendesk, Google Drive, Nexus/telemetry, email) into the existing AWS stack • Define and consume pre-aggregated account/opportunity summaries in S3 for fast, reliable query • Optimize Lambda-based data processing jobs for cost, reliability, and performance • Iterate on model strategy: cheap routing (e.g., Claude Haiku) vs. higher-quality response models (e.g., Claude Sonnet/Opus) • Evaluate prompts, tool selection quality, and response accuracy with clear metrics • Collaborate with GTM stakeholders (Sales, SE, CS, Product, Marketing) to define, test, and refine AI-assisted workflows • Partner with infra engineering (Terraform, Kubernetes) to ensure deployment, security, and observability are production-ready • Contribute to future UI/UX (Slack bot flows, simple web UI/dashboards) to expose workflows to end users