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Remote Phone Number Jobs in Kentucky (NOW HIRING)

Remote Phone Number information

What is the difference between Remote Phone Number vs Customer Service Representative?

AspectRemote Phone NumberCustomer Service Representative
Required credentialsNone specific, often basic tech skillsHigh school diploma or equivalent, sometimes certifications
Work environmentRemote, often from home or any location with internetRemote or in-office customer service centers
Employer industry usageTelecommunications, service providers, online platformsRetail, tech, healthcare, and service industries
Common search intentFinding contact numbers or virtual phone servicesSeeking customer support or service roles

Remote Phone Number typically refers to virtual or dedicated phone lines used for communication, while Customer Service Representatives handle customer inquiries via phone. Both roles involve communication skills, but their functions and credentials differ. Understanding these differences helps job seekers and employers find the right fit for their needs.

What are the key skills and qualifications needed to thrive as a remote customer service representative, and why are they important?

To thrive as a Remote Customer Service Representative, you need strong communication skills, problem-solving abilities, and typically a high school diploma or equivalent. Familiarity with CRM software, help desk platforms, and call center telephony systems is important for managing customer interactions efficiently. Patience, active listening, and time management are standout soft skills in this role. Mastering these skills ensures effective support, customer satisfaction, and productivity in a remote work environment.

What is a remote phone number?

A remote phone number is a telephone number that is not tied to a specific physical phone line or location. Instead, calls to this number can be forwarded to any device or location, such as a mobile phone, VoIP service, or another landline, making it ideal for businesses and individuals working remotely. Remote phone numbers can help maintain privacy, provide local presence in different regions, and enable flexible communication for remote teams. They are commonly used by businesses to manage calls efficiently and appear local to customers in different geographic areas.

What are some common challenges faced by professionals managing remote phone number services, and how can they be addressed?

Professionals managing remote phone number services often encounter challenges such as ensuring reliable connectivity, managing call forwarding settings, and maintaining security of client information. Addressing these challenges requires staying updated with the latest VoIP technologies, regularly testing number routing, and implementing robust authentication measures. Collaboration with IT and customer support teams is crucial to swiftly resolve technical issues and provide a seamless experience for users.
What are popular job titles related to Remote Phone Number jobs in Kentucky? For Remote Phone Number jobs in Kentucky, the most frequently searched job titles are:
What cities in Kentucky are hiring for Remote Phone Number jobs? Cities in Kentucky with the most Remote Phone Number job openings:
Infographic showing various Remote Phone Number job openings in Kentucky as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% Remote job distribution.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Louisville, KY • Remote

$112K - $147K/yr

Full-time

Posted 25 days ago


Job description

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.