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Remote Ai Agent Jobs in Indiana (NOW HIRING)

  • Retirement

Lead the design, development, and validation of simulation models (discrete-event, agent-based ... Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ...

$139K - $168K/yr

  • Medical

  • Dental

  • Vision

  • PTO

As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and ... At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ...

$139K - $168K/yr

  • Medical

  • Dental

  • Vision

  • PTO

As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and ... At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ...

$75K/yr

Cutting-Edge AI Training Get an edge on the competition with our new AI-driven training platform. You'll receive personalized feedback, interactive coaching, and real-time support to help you master ...

$75K/yr

Cutting-Edge AI Training Get an edge on the competition with our new AI-driven training platform. You'll receive personalized feedback, interactive coaching, and real-time support to help you master ...

Showing results 21-40

Remote Ai Agent information

How does a remote AI agent typically collaborate with cross-functional teams while working from different locations?

Remote AI Agents often work closely with data scientists, software engineers, and product managers through digital collaboration tools such as Slack, Zoom, and project management platforms like Jira or Asana. Effective communication and clear documentation are essential, as team members may be in different time zones. Regular virtual meetings and asynchronous updates help ensure alignment on project goals and tasks. Building strong remote relationships and proactively sharing progress or challenges are key to successful collaboration in this role.

How can I become a remote AI agent?

To become a remote AI agent, you typically need a strong understanding of artificial intelligence, machine learning, and related tools such as Python or TensorFlow. Gaining relevant experience through online courses, certifications, or projects, and demonstrating problem-solving skills are important for securing remote positions in this field.

What are the key skills and qualifications needed to thrive as a remote AI agent, and why are they important?

To thrive as a Remote AI Agent, you need a solid understanding of artificial intelligence concepts, problem-solving abilities, and typically a background in computer science or a related field. Familiarity with AI platforms, chatbot frameworks, and workflow automation tools is often required, along with experience using communication and ticketing systems. Strong written communication, adaptability, and self-motivation are crucial soft skills for excelling in a remote environment. These competencies ensure effective support, continuous learning, and high-quality interactions with clients or users in a technology-driven context.

What is a remote AI agent?

Remote AI agents are software programs or systems that utilize artificial intelligence to perform tasks or provide services from a remote location, often via the internet or cloud platforms. These agents can automate processes, analyze data, interact with users, or manage digital operations without the need for physical presence. Remote AI agents are commonly used in customer service, virtual assistance, technical support, and more, helping businesses improve efficiency and scalability. Their remote nature allows them to operate 24/7 and integrate seamlessly with various digital platforms.

What remote AI jobs can be done remotely?

Remote AI jobs include roles such as AI developer, machine learning engineer, data scientist, and AI research scientist. These positions often require skills in programming, data analysis, and familiarity with AI tools and frameworks, and they can typically be performed from any location with a reliable internet connection.

What is the difference between Remote Ai Agent vs Customer Support Specialist?

AspectRemote Ai AgentCustomer Support Specialist
Required CredentialsBasic technical knowledge, AI tools familiarityCustomer service skills, communication skills
Work EnvironmentRemote, AI-driven platformsRemote or on-site, customer interaction
Employer & Industry UsageTech companies, AI service providersRetail, telecom, service industries
Common Search & ComparisonAI automation, virtual assistanceCustomer service roles, support jobs

The main difference between a Remote Ai Agent and a Customer Support Specialist lies in their focus and tools. Remote Ai Agents primarily work with AI-driven platforms to assist or automate customer interactions, requiring some technical knowledge. Customer Support Specialists handle direct customer interactions, emphasizing communication skills. Both roles are often remote but serve different functions within customer service and tech industries.

What are the most commonly searched types of Ai Agent jobs in Indiana?

The most popular types of Ai Agent jobs in Indiana are:

What cities in Indiana are hiring for Remote Ai Agent jobs?

Cities in Indiana with the most Remote Ai Agent job openings:

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Indianapolis, IN โ€ข Remote

$117K - $154K/yr

Full-time

Re-posted 3 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.