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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and operating production distributed systems, with a strong focus on backend programming, cloud infrastructure, and observability. Proven ability to improve system reliability, scalability, and operational efficiency while mentoring teams in best practices for backend architecture.
Highest-signal resume keywords
Backend Programming Language ProficiencyDistributed Systems DesignCloud Infrastructure ManagementAPI Design and Data ModelingIncident Response and Post-Incident Analysis
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Asynchronous ProcessingMessage QueuesEvent-Driven SystemsIdempotencyConcurrencyDebugging SkillsSLOs and Error BudgetsWorkflow ExecutionObservability ToolsCapacity Planning
Soft Skills
MentoringCollaborationProblem-Solving
Tools & Technologies
KafkaPub/SubSQSGrafanaOpenTelemetrySentryKubernetesInfrastructure as CodeCloud-Native Deployment SystemsTemporal
Industry Keywords
HealthcareHIPAASOC 2SecurityPrivacyRegulated Environment
Tech Stack
Tools & technologiesCloudDistributed SystemsGrafanaKafkaKubernetes
About the role
Key responsibilities & impact- Design, build, and operate backend systems powering Ambient AI products across mobile and web
- Build inference workflows coordinating transcription, diarization, language models, clinical extraction, summarization, and other AI capabilities
- Develop orchestration systems for long-running, multi-stage workflows
- Implement scheduling, queueing, workload prioritization, retries, timeouts, fallbacks, dead-letter handling, idempotency, replay, recovery, model routing, versioning, progress tracking, and graceful degradation
- Improve reliability and scalability under variable, compute-intensive workloads
- Define and maintain SLOs for availability, processing latency, completion rates, and data durability
- Build observability through structured logging, metrics, distributed tracing, dashboards, alerting, and diagnostic tooling
- Lead incident response and post-incident analysis
- Identify systemic failure patterns and address them through abstractions, automation, testing, and architecture
- Improve cloud infrastructure, deployment systems, capacity planning, and operational tooling
- Design APIs and data models for safe, predictable interaction with long-running workflows
- Build tools for inspecting, testing, replaying, evaluating, and debugging inference pipelines
- Balance reliability, latency, quality, and infrastructure cost
- Partner with mobile, product, AI, security, and clinical teams
- Mentor engineers and establish practices for distributed systems, observability, operational readiness, and backend architecture
- Comply with information security policies and report confirmed or potential security events and risks
Requirements
What you’ll need- 8+ years of professional backend or infrastructure engineering experience
- Experience designing, building, and operating production distributed systems
- Strong proficiency in at least one modern backend programming language
- Experience with asynchronous processing, message queues, event-driven systems, or durable workflow execution
- Strong understanding of idempotency, consistency, concurrency, backpressure, retries, failure isolation, and eventual completion
- Experience operating services in a cloud environment, including deployment, monitoring, scaling, and incident response
- Experience designing APIs, service boundaries, and data models for complex product workflows
- Track record of improving system reliability, observability, scalability, or operational efficiency
- Strong debugging skills across application, infrastructure, data, and external dependency boundaries
- Ability to reason about real-time and long-running workloads with different latency and durability requirements
- Comfort working across backend, infrastructure, product, and AI systems
- Nice to have: speech-to-text, diarization, transcription, or audio-based machine-learning workflows
- Nice to have: large language models or multi-model inference pipelines in production
- Nice to have: Temporal or similar durable execution platforms
- Nice to have: Kafka, Pub/Sub, SQS, or similar messaging systems
- Nice to have: model routing, inference gateways, rate limiting, batching, caching, or GPU-backed workloads
- Nice to have: workflow inspection, replay, evaluation, or model debugging tooling
- Nice to have: SLOs, error budgets, alerting, and production incident response
- Nice to have: Grafana, OpenTelemetry, Sentry, or similar observability tools
- Nice to have: containers, Kubernetes, infrastructure as code, and cloud-native deployment systems
- Nice to have: throughput, tail latency, infrastructure cost, and workload isolation optimization
- Nice to have: offline clients, background synchronization, or delayed and duplicated event reconciliation
- Nice to have: healthcare, HIPAA, SOC 2, encryption, privacy, security, or regulated-environment experience
- Nice to have: AI-native, real-time, or agentic product experience
- Position requires being in the San Francisco, CA or Mountain View, CA office at least 3 days per week
- Must answer whether sponsorship to work in the US will be required
Benefits
Comp & perks- Equity
- Opportunity to build an AI healthcare product used in real clinical workflows
- Grow into broader backend, infrastructure, or technical leadership
- Official company communications exclusively from @commure.com email addresses