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From Home Ai Coding Jobs in Virginia (NOW HIRING)

Humana Inc

Inpatient Medical Coding Auditor

Richmond, VA · On-site

$71.10 - $97.80/hr

The Inpatient Medical Coding Auditor work assignments involve moderately complex to complex issues ... If you are looking to work from home, for a Fortune 100 company that focuses on the well-being of ...

Jobtailor

Software Engineer - Deployment

Arlington, VA · On-site

$140 - $210/hr

... application, leveraging AI coding assistants to accelerate development. * Lead the active ... Communicate and work collaboratively with colleagues and lead engineers from other disciplines

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From Home Ai Coding information

What is the difference between From Home Ai Coding vs From Home Data Scientist?

AspectFrom Home Ai CodingFrom Home Data Scientist
Required CredentialsProgramming skills, AI/ML knowledge, certifications in AI or codingStatistics, programming, data analysis certifications, advanced degrees often preferred
Work EnvironmentRemote, tech-focused, project-basedRemote, research-oriented, data-driven projects
Employer & Industry UsageTech companies, startups, AI-focused firmsTech, finance, healthcare, research institutions
Search & Comparison IntentFocus on AI coding tasks, machine learning projectsData analysis, insights, statistical modeling

From Home Ai Coding primarily involves developing and implementing AI algorithms and models remotely, requiring coding and AI expertise. In contrast, From Home Data Scientist focuses on analyzing data to extract insights, often using statistical and analytical skills. Both roles are remote and tech-centric but differ in their core responsibilities and skill sets.

What jobs can I do from home using AI?

From home AI-related jobs include roles such as AI data annotator, machine learning engineer, AI content creator, chatbot developer, and AI support specialist. These positions often require skills in programming, data analysis, and familiarity with AI tools and platforms, and they typically offer flexible schedules and remote work environments.

What are the most commonly searched types of Ai Coding jobs in Virginia?

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For From Home Ai Coding jobs in Virginia, the most frequently searched job titles are:

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From Home Ai Coding jobs near you
Infographic showing various From Home Ai Coding job openings in Virginia as of June 2026, with employment types broken down into 78% Full Time, 12% Part Time, 5% Temporary, and 5% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Richmond, VA • On-site

$150 - $230/hr

Other

Re-posted 8 days ago

Job description

Senior Software Engineer: Applied AI (Voice Agents & ML Systems) 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
  • 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
  • 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.

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
  • Your LinkedIn profile URL
  • A phone number where we can reach you

A resume is welcome but optional; the two items above are required.

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