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Ai Rag Jobs in Florida (NOW HIRING)

Scalence L.L.C.

Gen AI Tech Lead

Tampa, FL · On-site

$132K - $162K/yr

Responsibilities : • Design scalable, maintainable AI solutions that integrate Langchain, LangGraph, and RAG methodologies to enhance knowledge discovery and conversational AI capabilities. • ...

Tror AI for everyone

AI Engineer

Lake Mary, FL · On-site

AI Engineer Job Location: Lake Mary, FL (3 Days Onsite) Job Type: Contract Need 11+ Years of ... Retrieval-Augmented generation (RAG) * Document Ingestion and preprocessing * Chunking Strategies ...

Channel Partners

Senior AI Application Engineer

Tampa, FL · On-site +1

$120K - $140K/yr

Demonstrated experience building and deploying RAG systems -- including vector database selection, chunking strategies, hybrid search, and evaluation pipelines. * Experience with agentic AI ...

QUANTUM TECHNOLOGIES LLC

AI Data Engineer

Tallahassee, FL · On-site

$90/hr

AI Data Engineer Location: Tallahassee, FL, USA Duration: 12 Months + Extension Bill Rate: $90/hr ... Develop and optimize RAG (Retrieval-Augmented Generation) data pipelines using vector databases and ...

New

WAI GLOBAL

Analyst, AI Engineer

Hollywood, FL · On-site

Build and support retrieval-augmented generation (RAG), embeddings, vector search, document ingestion pipelines, prompt workflows, and AI assistant capabilities for internal users and distributor ...

Capco

Mid Level AI Engineer

Orlando, FL · Hybrid

Develop and optimize Retrieval-Augmented Generation (RAG) solutions leveraging vector databases and enterprise knowledge sources. * Create intelligent AI agents and workflows capable of interacting ...

VIS IT Solutions Inc

AI Architect

Miami, FL · On-site

Miami, FL Duration: 6 months GBaMS ReqID: 10641871 JD: • 10-15 years in AI, ML, or enterprise architecture roles. • Proven track record architecting RAG systems, vector search, and LLM-based ...

Merican Inc

AI Solution Architect

Town N Country, FL · On-site

$57 - $75/hr

Retrieval-Augmented Generation (RAG) * Semantic Search * MLOps Tools * Cloud-Native Architecture * Microservices * Kubernetes * Agile Delivery Job Summary We are seeking an experienced AI Solution ...

Brillius

AI Architect

Miami, FL · On-site

... RAG systems, vector search, and LLM-based knowledge platforms. • Strong hands-on experience with: o Python o Cloud ML platforms-Azure o Vector DBs (Pinecone, DB Vector) o LangChain / LlamaIndex or ...

Vaco by Highspring

AI Engineer

Jacksonville, FL · On-site

Basic RAG implementations (embeddings + vector search for retrieval-augmented generation) * Strong discipline around AI evaluation and reliability , including: * Testing prompts and multi-step chains

Inficare Technologies

AI Engineer

Sunrise, FL · On-site

Experience with LangGraph, RAG, or MCP-style integrations * Hands-on experience with generative AI and prompt engineering * Experience with CI/CD pipelines and containerized deployments Preferred ...

Nous Infosystems

AI Solution Architect

Tampa, FL · On-site

$57.25 - $75.50/hr

... RAG, semantic search, MLOps tools, cloud-native architecture, microservices, Kubernetes, agile delivery Job Summary: The Onsite AI Solution Architect will lead the end-to-end architecture, design ...

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Ai Rag information

What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

Which AI is best at RAG?

For an AI Rag role, the best AI systems for Retrieval-Augmented Generation (RAG) tasks typically include models like OpenAI's GPT-4, Google's Bard, and Meta's Llama 2, which are capable of integrating retrieval components with language generation. Success in RAG depends on the model's ability to efficiently access and incorporate external data, as well as the implementation of effective retrieval mechanisms and fine-tuning. Skills in natural language processing, knowledge of retrieval systems, and experience with relevant tools are essential for this role.

What engineer makes 500,000 a year?

Senior software engineers, especially those working in high-demand fields like artificial intelligence or machine learning at large tech companies, can earn $500,000 or more annually. Compensation often includes base salary, bonuses, and stock options, and requires advanced skills, extensive experience, and often a master's or Ph.D. in a related field.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in data science, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong track record of innovation and leadership in the field.

What are AI RAGs?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

Which 3 jobs will survive AI?

AI Rag is a role that involves managing and interpreting AI outputs, and jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to survive AI automation. Examples include healthcare professionals, skilled tradespeople, and roles in education. These jobs often require human judgment, interpersonal skills, and adaptability that AI cannot fully replicate.

What are some common challenges faced by AI RAG (Retrieval-Augmented Generation) engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What job categories do people searching Ai Rag jobs in Florida look for? The top searched job categories for Ai Rag jobs in Florida are:
What cities in Florida are hiring for Ai Rag jobs? Cities in Florida with the most Ai Rag job openings:
Ai Rag jobs near you
Staff AI Engineer

Staff AI Engineer

Modernizing Medicine, Inc.

Boca Raton, FL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago

Job description

Join the Team Modernizing Medicine
At ModMed, we're not just building software-we're reimagining the healthcare experience. Founded in 2010 by a practicing physician and a successful tech entrepreneur, we took a radically different approach: we hired doctors and taught them how to code. This "for doctors, by doctors" philosophy has allowed us to create an AI-enabled, specialty-specific cloud platform that places patients at the center of care.
A Culture of Excellence
When you join ModMed, you're joining an award-winning team recognized for innovation and employee satisfaction. From our global headquarters in Boca Raton Florida, and extensive employee base in Hyderabad India, we are a team of 4,500+ passionate problem-solvers on a mission to increase medical practice success and improve patient outcomes:
  • Consistently ranked as a Top Place to Work
  • 2025 Globee Business Awards: Gold Globee for "Technology Team of the Year"
  • 2025 Black Book Awards: Ranked #1 EHR in 11 Specialties
  • Florida Venture Forum: Venture-Backed Company of the Year

We are growing fast, thinking big, and we are just getting started.
Ready to modernize medicine with us?
Job Description Summary:
As a Staff AI Engineer, you define and drive the architecture of AI and agentic systems across multiple teams and product domains. This is a senior individual-contributor leadership role: you influence high-impact architectural decisions, evolve the practices and standards for building agentic AI, and turn experimental AI capabilities into reliable production systems. You set direction for multi-agent orchestration, production RAG (hybrid search, re-ranking, and query routing), tool and MCP integration, and the evaluation and observability stack that keeps them dependable. You mentor senior engineers and represent AI engineering in cross-functional and strategic initiatives. A background in classical ML is an asset; the primary requirement is a proven track record of shipping production agentic AI.
KEY RESPONSIBILITIES
  • Define and drive technical direction for AI and agentic systems, and contribute to the AI platform roadmap across teams
  • Influence architecture decisions for compute, cloud, and AI infrastructure across teams
  • Lead the design of large-scale AI/LLM systems: inference platforms, APIs, and distributed architectures
  • Architect production multi-agent systems end-to-end: orchestration, state management, tool integration, and failure handling
  • Define and drive best practices and standards for AI/LLM systems across teams (agent design, evaluation, observability, reliability)
  • Lead complex production debugging and incident response across teams, and harden the resulting fixes into platform guardrails
  • Mentor senior engineers and emerging technical leaders, raising the engineering bar
  • Lead technical design reviews and architecture decision records (ADRs) for critical AI infrastructure
  • Contribute to capacity planning and cost optimization strategies for AI/LLM infrastructure

GENAI / AGENTIC AI CAPABILITIES
  • Define and drive vector database and RAG architecture decisions across systems and teams: structured RAG, hybrid search (dense + sparse + keyword), re-ranking, and query routing
  • Lead multi-agent platform architecture decisions: runtime selection, orchestration patterns, and enterprise integration strategy
  • Set the technical direction for MCP (Model Context Protocol) adoption and agent runtime infrastructure
  • Shape agent infrastructure adoption: evaluate and standardize frameworks, tooling, and deployment patterns for agentic AI
  • Architect evaluation infrastructure for non-deterministic LLM systems: synthetic golden-set generation, hierarchical weighted scoring (component, composite, and system-level F1), bootstrap confidence intervals, and paired A/B comparison, treating a change as real only when it is both statistically significant and clears a minimum effect size
  • Gate deployments on eval results: tiered regression thresholds (hard-gate vs monitor components) wired into CI so a measurable quality regression blocks the release, with observability via tracing across multi-step chains and tool calls and drift detection on LLM inputs and outputs
  • Drive LLM cost optimization at scale: model routing, caching, batching, token budget management, and provider cost analysis

REQUIRED SKILLS & QUALIFICATIONS
  • Master's or Ph.D. degree in Computer Science, Software Engineering, or a related field.
  • 10+ years of professional experience in ML/AI or software engineering, including 4+ years in senior or staff-level roles with production system ownership
  • Demonstrated engineering leadership, including driving technical strategy and influencing cross-team decisions
  • Expertise in platform and distributed-systems architecture at scale: model serving, APIs, data platforms, and AI/LLM infrastructure
  • Hands-on experience architecting and operating production agentic AI or LLM systems (multi-agent workflows, production RAG, tool and MCP integration)
  • Deep understanding of embedding models, retrieval algorithms, and vector database internals
  • Strong production debugging, reliability, and incident-response skills
  • Experience building rigorous evaluation for non-deterministic AI systems, including statistical methods (such as bootstrap confidence intervals and minimum effect-size thresholds) to separate genuine quality changes from run-to-run model variance
  • Cost-awareness for cloud AI/LLM workloads: capacity planning and cost optimization
  • Proven mentorship of mid-level and senior engineers
  • Strong communication skills for executive and cross-functional audiences

PREFERRED QUALIFICATIONS (NICE TO HAVE)
  • Experience in Healthcare, FinTech, or other regulated industries
  • Experience building AI/LLM systems or platform components from the ground up
  • Defined best practices for AI-assisted development (Claude Code): code quality standards, review, and responsible usage across teams
  • Track record of conference talks, published papers, or significant open-source contributions
  • Experience with GPU-accelerated inference and model serving optimization
  • Familiarity with workflow orchestration and streaming architectures for real-time AI

ModMed Benefits Highlight: At ModMed, we believe it's important to offer a competitive benefits package designed to meet the diverse needs of our growing workforce. Eligible Modernizers can enroll in a wide range of benefits:
United States
  • Comprehensive medical, dental, and vision benefits, including a company Health Savings Account contribution,
  • 401(k): ModMed provides a matching contribution each payday of 50% of your contribution deferred on up to 6% of your compensation. After one year of employment with ModMed, 100% of any matching contribution you receive is yours to keep.
  • Generous Paid Time Off and Paid Parental Leave programs,
  • Company paid Life and Disability benefits, Flexible Spending Account, and Employee Assistance Programs,
  • Company-sponsored Business Resource & Special Interest Groups that provide engaged and supportive communities within ModMed,
  • Professional development opportunities, including tuition reimbursement programs and unlimited access to LinkedIn Learning,
  • Global presence and in-person collaboration opportunities; dog-friendly HQ (US), Hybrid office-based roles and remote availability for some roles,
  • Weekly catered breakfast and lunch, treadmill workstations, Zen, and wellness rooms within our BRIC headquarters.

PHISHING SCAM WARNING: ModMed is among several companies recently made aware of a phishing scam involving imposters posing as hiring managers recruiting via email, text and social media. The imposters are creating misleading email accounts, conducting remote "interviews," and making fake job offers in order to collect personal and financial information from unsuspecting individuals. Please be aware that no job offers will be made from ModMed without a formal interview process, and valid communications from our hiring team will come from our employees with a ModMed email address (first.lastname@modmed.com). Please check senders' email addresses carefully. Additionally, ModMed will not ask you to purchase equipment or supplies as part of your onboarding process. If you are receiving communications as described above, please report them to the FTC website.

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