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Ai Rag Jobs in Florida (NOW HIRING)

Worth AI

Senior Agentic (AI) Engineer

Tampa, FL · On-site +1

$98.80K - $135.60K/yr

Worth AI is hiring a Senior Agentic AI Engineer to design and ship production agent systems that ... Strong RAG fundamentals chunking, embeddings, hybrid retrieval, reranking, grounding - and judgment ...

Virtusa Corporation

Sr. Gen AI Developer

Tampa, FL · On-site

$114.80K - $154.50K/yr

Proven experience designing and delivering LLM / GenAI solutions (e.g., RAG, orchestration, prompt engineering, AI-assisted automation). Solid understanding of microservices, APIs, distributed ...

Total Quality Logistics

AI Architect

Tampa, FL · On-site

Experience with embeddings, vector databases, RAG patterns, LangChain, Semantic Kernel and MLflow ... AI Strategy & Enterprise Architecture * Evaluate and recommend AI models, APIs and platforms (e.g ...

Tata Consultancy Service Limited

AI Developer

Tampa, FL · On-site

$100K - $130K/yr

Neural Networks, Decision Trees, SVM, NLP, Reinforcement Learning, Ensemble Methods, MCP • Strong knowledge with RAG (Retrieval-Augmented Generation), Prompt Engineering, Agentic AI • Knowledge ...

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 ...

TQL

AI Architect

Tampa, FL

$59.50 - $78.50/hr

Hands-on experience with Azure OpenAI, Azure Machine Learning, Azure AI Search, Microsoft Fabric and Lakehouse architectures Experience with embeddings, vector databases, RAG patterns, LangChain ...

Virtusa

Sr. Gen AI Developer

Tampa, FL

$114.80K - $154.50K/yr

Proven experience designing and delivering LLM / GenAI solutions (e.g., RAG, orchestration, prompt ... Strong foundation in secure coding practices and performance optimizatio AI & GenAI Experience ...

Virtusa

Sr. Gen AI Developer

Tampa, FL

$114.80K - $154.50K/yr

Proven experience designing and delivering LLM / GenAI solutions (e.g., RAG, orchestration, prompt ... Strong foundation in secure coding practices and performance optimizatio AI & GenAI Experience ...

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 ...

Blue Prism Group

Director of CX AI

Jacksonville, FL

Director of CX AI SS&C Advent delivers technology solutions that power some of the world's most ... Technical Leadership -- Serve as a hands-on architecture authority across LLM, RAG, and agentic ...

Guru Schools

Senior/Lead AI Engineer

Orlando, FL · On-site

Develop fine-tuned and optimized large language model applications with retrieval-augmented generation (RAG) pipelines. * Integrate with Enterprise Platforms: Embed AI capabilities into OMS, CRM, ...

Purple Drive Technologies

AI Architect

Miami, FL · On-site

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

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 ...

Dlapiper

AI Solutions Engineer

Miami, FL · Hybrid

Summary The AI Solutions Engineer is an embedded partner to the Professional Excellence (PE ... Understanding of ML models, ability to select the correct models and solution patterns, various RAG ...

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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 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 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.

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.

What are popular job titles related to Ai Rag jobs in Florida? For Ai Rag jobs in Florida, the most frequently searched job titles are:
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

Senior Agentic (AI) Engineer

Worth AI

Tampa, FL • On-site, Remote

$98.80K - $135.60K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago

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

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