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Senior Software Engineer – Applied AI
AMC HealthSenior Software Engineer building and operating AI voice agents in a regulated healthcare setting. Involves real-time systems, LLM engineering, machine learning, and cloud infrastructure.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in building and operating production backend systems, with a strong focus on Python programming and hands-on production experience with LLMs or generative AI. Capable of managing the traditional machine learning lifecycle while ensuring compliance in a regulated environment.
Highest-signal resume keywords
Python ProgrammingProduction Backend SystemsLLM ExperienceDistributed SystemsMachine Learning Lifecycle
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Production Backend SystemsPython ProgrammingLLM ExperienceMachine Learning LifecycleDebuggingTelemetry AnalysisControl Systems DesignMetric Anomaly TracingBatch-Analysis PipelinesVendor Issue Resolution
Soft Skills
Judgment in Model UsageDisciplined Approach
Tools & Technologies
Cloud SystemsReal-Time Voice PipelineTelemetry ToolsEvaluation PipelinesControl Systems
Industry Keywords
Generative AIRegulated EnvironmentData HandlingProduction InferenceSafe Fallbacks
Tech Stack
Tools & technologiesCloudDistributed SystemsPython
About the role
Key responsibilities & impact- Ship and debug code on a live, real-time voice pipeline where latency and correctness are user-facing
- Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
- Build and operate LLM evaluation and batch-analysis pipelines
- Own traditional ML workflows from data to scheduled production inference
- Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor
Requirements
What you’ll need- 7+ years building and operating production backend systems
- Strong general-purpose programming skills (we work primarily in Python)
- Experience running distributed systems in the cloud; comfortable debugging from telemetry to root cause
- Hands-on production experience with LLMs or generative AI (any provider or framework), plus the judgment to know when not to use a model
- Working fluency across the traditional machine learning lifecycle (you productionize; you do not need to publish)
- Disciplined in a regulated environment: small, reviewable changes and careful handling of sensitive data
Benefits
Comp & perks- Health insurance
- 401(k) matching
- Paid time off
- Flexible work arrangements