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Intern Remote Ai Prompt Engineer Jobs in Florida

Worth AI

Senior Agentic (AI) Engineer

Miami, FL · On-site +1

$99K - $137K/yr

Mentor engineers on agent patterns, prompt hygiene, eval discipline, and LLM failure modes ... All Remote Hires will be required to travel to Orlando, Florida at least twice per year for Town ...

Boats Group

AI Software Engineer

Miami, FL · On-site +1

Understanding of prompt engineering, retrieval-augmented reasoning, and tool orchestration ... Embrace a balanced work model with remote work on Mondays and Fridays and in-office collaboration ...

Epiq

Lead AI Software Engineer

Tampa, FL · Remote

Apply prompt engineering techniques to optimize model interactions and outcomes. * Ensure ... LI-Remote The Compensation range for this role is 120,000 to 170,000 USD annually and may be ...

Kemper

Guidewire Developer-ClaimCenter

Jacksonville, FL · On-site +1

$50.50 - $66.75/hr

... TX, Remote-CT, Remote-GA, Remote-IL, Remote-IN, Remote-OH, Remote-PA, Remote-TX, Remote-VA ... AI Prompt/Agentic Engineering * Monitoring and logging via tools like AppDynamics and Splunk

Kemper

Guidewire Developer-ClaimCenter

Tampa, FL · On-site +1

$51.50 - $68/hr

... TX, Remote-CT, Remote-GA, Remote-IL, Remote-IN, Remote-OH, Remote-PA, Remote-TX, Remote-VA ... AI Prompt/Agentic Engineering * Monitoring and logging via tools like AppDynamics and Splunk

IntelePeer

AI Agent Engineer

Dania Beach, FL · On-site +1

$102K - $137K/yr

... including prompt engineering and retrieval-augmented generation (RAG) patterns in production ... Locations Dania Beach, FL, Centennial, CO, Remote USA Remote status Fully Remote Yearly salary 95 ...

Kobie Marketing

AI Engineer

Saint Petersburg, FL

As a remote-first organization headquartered in St. Petersburg, Florida, Kobie values meaningful in ... Implement guardrails around tool execution: auth scoping, input/output validation, PII and prompt ...

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Intern Remote Ai Prompt Engineer information

What is the difference between Intern Remote Ai Prompt Engineer vs Intern Remote Data Annotator?

AspectIntern Remote Ai Prompt EngineerIntern Remote Data Annotator
Required CredentialsBasic understanding of AI, programming, or related courseworkAttention to detail, basic computer skills
Work EnvironmentRemote, collaborative with AI teamsRemote, often independent annotation tasks
Industry UsageAI development, NLP projectsData labeling for machine learning
Search & Comparison IntentUnderstanding AI prompt roles, entry-level AI jobsData annotation roles, entry-level data jobs

The Intern Remote Ai Prompt Engineer focuses on creating and refining prompts for AI models, requiring some technical knowledge. In contrast, the Intern Remote Data Annotator primarily labels data to train AI systems, emphasizing accuracy and attention to detail. Both roles are remote and entry-level, but they serve different functions within AI development teams.

What types of projects and responsibilities can I expect as a remote AI prompt engineer intern?

As a remote AI Prompt Engineer intern, you can expect to work on tasks such as designing, testing, and refining prompts for large language models to improve their accuracy and relevance. You'll likely collaborate with data scientists, software engineers, and other team members to analyze AI model outputs and iterate on prompt strategies. Typical responsibilities may also include documenting best practices, participating in team meetings, and contributing to ongoing research or product development. This role offers a hands-on learning experience in AI development while working in a supportive, remote environment.

What are the key skills and qualifications needed to thrive as a remote AI prompt engineer intern?

To thrive as an Intern Remote AI Prompt Engineer, you need a solid understanding of natural language processing concepts, critical thinking skills, and preferably some background in computer science or linguistics. Familiarity with AI platforms like OpenAI, prompt engineering tools, and collaborative work systems (such as GitHub or Slack) is commonly expected. Strong written communication, creativity, and adaptability are valuable soft skills for crafting effective prompts and collaborating with distributed teams. These skills are crucial for generating high-quality AI outputs and ensuring productive teamwork in a remote environment.

What does a remote AI prompt engineer intern do?

A Remote AI Prompt Engineer Intern works on designing, testing, and refining prompts for artificial intelligence models, particularly those used in natural language processing. Their main responsibility is to craft effective prompts that optimize AI responses for accuracy and relevance. They may also analyze AI outputs, collaborate with teams to improve model performance, and document best practices. Since the role is remote, communication and self-management skills are essential. This internship provides valuable experience in AI development and prompt engineering.

What are the most commonly searched types of Remote Ai Prompt Engineer jobs in Florida?

The most popular types of Remote Ai Prompt Engineer jobs in Florida are:

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Intern Remote Ai Prompt Engineer jobs near you
Infographic showing various Intern Remote Ai Prompt Engineer job openings in Florida as of August 2026, with employment types broken down into 76% Full Time, 19% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 65% Physical, 4% Hybrid, and 31% Remote job distribution.

Senior Agentic (AI) Engineer

Worth AI

Miami, FL • On-site, Remote

$99K - $137K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted yesterday

Job description

Worth AI is hiring a Senior Agentic AI Engineer to design and ship production agent systems that automate KYB, underwriting, and risk decisions on regulated financial data. You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams.

Responsibilities
  • Design and ship multi-step agentic systems (planner/executor, tool-using, multi-agent, human-in-the-loop) for onboarding, underwriting, case review, and continuous monitoring.
  • Architect agent graphs in LangGraph (or comparable - CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks.
  • Build the retrieval layer powering our agents - chunking, hybrid search, reranking, and grounded citation.
  • Own the eval stack: golden sets, offline regression suites, LLM-as-judge, online A/B and shadow evals, and red-teaming for jailbreaks, prompt injection, and PII leakage.
  • Expose agents to production systems via well-typed tools and MCP servers. Treat tool surface area as a product.
  • Drive production MLOps: deployment, versioning, traffic shaping, cost/latency budgets, tracing, and on-call playbooks for agent incidents.
  • Partner with security and compliance to keep agents inside SOC 2, GDPR, CCPA, and fair-lending posture - auditability and explainability built in, not bolted on.
  • Mentor engineers on agent patterns, prompt hygiene, eval discipline, and LLM failure modes.
  • Technology Stack
    • Languages: Python, Node.js, TypeScript
    • Agent / LLM frameworks: LangGraph, LangChain, Claude Agent SDK, MCP, OpenAI SDK
    • Models: Anthropic Claude, OpenAI, open-weight where appropriate
    • Retrieval & Data: PostgreSQL, pgvector, OpenSearch, Kafka, Redshift, Redis
    • Infra: AWS, Kubernetes (EKS), ArgoCD, Terraform
    • Evals & Observability: LangSmith / Langfuse / Braintrust-style tooling, DataDog

Requirements

  • 5+ years of software engineering experience, with 2+ years building production LLM or agentic systems (not just notebooks or demos).
  • Hands-on experience with a modern agent framework (LangGraph strongly preferred) and a track record of shipping agents that run, fail gracefully, and recover.
  • Strong RAG fundamentals chunking, embeddings, hybrid retrieval, reranking, grounding - and judgment about when RAG isn't the right answer.
  • Real eval experience golden sets, offline and online evaluations, used to make ship/no-ship calls.
  • Production MLOps fluency: deployed LLM workloads under real latency, cost, and reliability constraints.
  • Strong Python; comfortable in TypeScript / Node.js.
  • Solid systems engineering instincts APIs, async patterns, queues, databases, distributed system failure modes.
  • Calibrated communicator; thrives in ambiguous, fast-moving environments.
  • Prior experience in fintech, lending, payments, KYB/KYC, fraud, or AML.
  • Experience building MCP servers or other structured tool interfaces for LLMs.
  • Background in classical ML (ranking, scoring, calibration).
  • Experience designing explainable / auditable AI workflows for regulated environments.
  • Open-source contributions to agent frameworks, eval tooling, or retrieval libraries.
  • AWS depth (EKS, MSK, RDS, S3, Lambda) and IaC with Terraform.
Success Metrics
  • Agent Quality: Measurable improvements in task success rate, grounding accuracy, and hallucination rate on our eval suites.
  • Production Reliability: Agents you own meet defined SLOs for latency (P90/P99), tool-call success, and cost per task.
  • Velocity: New agent capabilities go from prototype to production in weeks, without skipping evals or guardrails.
  • Risk Posture: Zero material incidents tied to prompt injection, PII leakage, or unsafe tool use on agents you own.
  • Force Multiplier: Patterns, tools, and eval scaffolding you build get adopted across engineering.

All Remote Hires will be required to travel to Orlando, Florida at least twice per year for Town Halls and team collaboration, in addition to orientation in Orlando.

Benefits

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Life Insurance
  • Flexible Paid Time Off
  • 9 paid Holidays
  • Family Leave
  • Remote
  • Hybrid work (for Orlando Associates)
  • Free Food & Snacks (Orlando)
  • Wellness Resources

Apply