Senior Software Engineer: Applied AI (Voice Agents & ML Systems)
AMC Health · Remote (US) · Full-time
The pitch
We build and operate production AI voice agents that hold real phone conversations in a regulated healthcare setting, plus the machine learning and LLM pipelines around them. This is one seat that spans four disciplines that rarely come together: real-time systems, LLM engineering, traditional machine learning, and serious cloud infrastructure, all in production, all with real consequences. If you are the kind of engineer who gets restless doing one thing, this role is the opposite problem.
What you'll work across
Real-time voice AI
- Streaming, low-latency speech-to-speech systems built on modern LLMs
- Telephony and real-time media (call control, live audio streaming)
- Audio handling and the quirks of real human conversation (interruptions, timing, noise)
- Concurrency on a latency-sensitive path, where p99 matters and a stall is something a caller hears
LLM engineering
- Wrapping nondeterministic models in deterministic control so they behave reliably in production
- Multi-model pipelines, prompt design, and cost/latency budgeting
- Evaluation harnesses, including LLM-as-judge and automated agent-tests-agent approaches
- Agentic tooling that gives AI systems safe, structured access to infrastructure
Traditional (non-LLM) machine learning
- End-to-end ML pipelines: feature engineering, model training, and scheduled inference
- Imbalanced, messy real-world data; calibration and explainability for non-technical consumers
- Turning research notebooks into reproducible, auditable production pipelines
Cloud and infrastructure
- Infrastructure as code across multiple environments (we run on AWS)
- Managed compute, data, streaming, and orchestration services
- Security engineering in a regulated setting: encryption, least-privilege access, strict data-handling discipline
- Observability and telemetry-driven debugging, tracing a production issue from a metric anomaly to root cause
Plus occasional full-stack work on internal tools, and an engineering workflow that leans heavily on AI coding assistants, with human accountability for every change.
What you'll actually do
- 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
Must-haves
- 7+ years building and operating production backend systems, with 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
Nice-to-haves
- Real-time media or telephony experience
- Front-end / full-stack ability
- ML pipeline experience, vector search, or embeddings
- Fluency with AI coding assistants (our workflows assume them, with human accountability for every change)
How we work
Smallest correct change wins. Every behavior change is validated against the live system. Evidence over opinion in debugging. Code review is rigorous. Safety and privacy gate everything.
Work authorization (no exceptions)
This role is open only to US citizens and lawful permanent residents (Green Card holders). We cannot consider candidates who require visa sponsorship now or in the future, and we are unable to make exceptions of any kind.
How to apply
Please submit both of the following:
- Your LinkedIn profile URL
- A phone number where we can reach you
A resume is welcome but optional; the two items above are required.
Skills Required
- 7+ years building and operating production backend systems with strong general-purpose programming skills (primarily Python)
- Experience running distributed systems in the cloud and debugging from telemetry to root cause (AWS)
- Hands-on production experience with LLMs or generative AI (any provider or framework)
- Working fluency across the traditional machine learning lifecycle (feature engineering, training, production inference)
- Discipline working in a regulated environment with careful data handling and small, reviewable changes
- Real-time media or telephony experience
- Front-end or full-stack ability
- ML pipeline experience, vector search, or embeddings
- Fluency with AI coding assistants
What We Do
AMC Health is a virtual care and remote patient monitoring company serving health plans, health systems, hospitals, and government programs. Its end-to-end solution combines in-home medical devices, real-time physiometric data, predictive AI and analytics, and nurse-led clinical care to support earlier intervention, reduce care gaps, and improve outcomes for people managing chronic conditions at home. The company has operated since 2002 and staffs U.S.-based clinical teams.
