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Ai Implementation Jobs in Florida (NOW HIRING)

AI Solutions Architect

Tampa, FL · On-site

$59.50 - $78.50/hr

Responsibilities : • Lead technical discovery for PRESHos and AI implementation opportunities. • Translate client goals, workflows, pain points, and system constraints into clear technical ...

Your work will involve designing AI systems, data wrangling, and software implementation to enable scalable AI models, promoting technological advances where people and technology thrive together.

Your work will involve designing AI systems, data wrangling, and software implementation to enable scalable AI models, promoting technological advances where people and technology thrive together.

Your work will involve designing AI systems, data wrangling, and software implementation to enable scalable AI models, promoting technological advances where people and technology thrive together.

Your work will involve designing AI systems, data wrangling, and software implementation to enable the AI models to be useful and scalable. As a Senior Associate, you will focus on building ...

Director, Implementation

Miami, FL · On-site

$180 - $230/hr

We offer an AI-powered, SaaS platform connecting Fresh, Center, eCommerce, and DSD department ... Role Overview Upshop is seeking a Director of Implementation to lead our Implementation ...

Director, Implementation

Miami, FL · On-site

$180 - $240/hr

We offer an AI-powered, SaaS platform connecting Fresh, Center, eCommerce, and DSD department ... Role Overview Upshop is seeking a Director of Implementation to lead our Implementation ...

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Ai Implementation information

How to get into AI implementation?

To pursue a career in AI implementation, develop strong skills in programming languages such as Python, understand machine learning frameworks like TensorFlow or PyTorch, and gain experience with data analysis and model deployment. Earning relevant certifications or degrees in computer science, data science, or AI can also enhance your qualifications.

What are the key skills and qualifications needed to thrive in the AI implementation position?

To excel in AI Implementation, you need a robust understanding of machine learning concepts, data analysis, and software development, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, cloud platforms (AWS, Azure), and AI integration frameworks is commonly required, along with relevant certifications. Strong project management, problem-solving abilities, and excellent communication skills are crucial for coordinating with stakeholders and driving adoption. Mastering both technical and interpersonal skills ensures projects are delivered effectively and meet business objectives within diverse organizational settings.

What is an AI implementation?

An AI Implementation job involves deploying artificial intelligence solutions within an organization to improve efficiency, automation, and decision-making. Professionals in this role work closely with data scientists, engineers, and business teams to integrate AI models into existing systems. They manage data pipelines, ensure model performance, and address challenges related to scalability and compliance. Strong technical skills, project management, and an understanding of business processes are essential for success in this role.

What kinds of teams and departments does an AI implementation professional typically collaborate with?

AI Implementation professionals usually work cross-functionally, interacting with data scientists, software engineers, IT departments, and business stakeholders to ensure AI solutions address specific business needs. Regular collaboration with product managers and operations teams helps align technical efforts with strategic objectives and regulatory requirements. You may also work closely with end users to gather feedback, refine implementations, and ensure a smooth adoption process. This collaborative environment not only enhances the quality of AI deployments but also offers valuable exposure to different aspects of the organization, fostering professional growth.

How to become an AI implementation specialist?

To become an AI implementation specialist, individuals typically need a strong background in computer science, data science, or related fields, along with knowledge of AI and machine learning algorithms. Gaining experience with programming languages like Python, familiarity with AI frameworks such as TensorFlow or PyTorch, and understanding of deployment environments are essential. Certifications in AI or cloud platforms can also enhance job prospects in this role.
What are the most commonly searched types of Ai Implementation jobs in Florida? The most popular types of Ai Implementation jobs in Florida are:
What job categories do people searching Ai Implementation jobs in Florida look for? The top searched job categories for Ai Implementation jobs in Florida are:
What cities in Florida are hiring for Ai Implementation jobs? Cities in Florida with the most Ai Implementation job openings:
Infographic showing various Ai Implementation job openings in Florida as of August 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% In-person job distribution.

AI Solutions Architect

PRESHai

Tampa, FL • On-site

$59.50 - $78.50/hr

Full-time

Re-posted 6 days ago


Job description

Job Summary:
PRESHai is a company focused on AI solutions, and they are seeking an AI Solutions Architect to lead the technical architecture and integration of client implementations. The role involves designing AI systems, guiding engineers, and ensuring successful client integration.
Responsibilities:
• Lead technical discovery for PRESHos and AI implementation opportunities.
• Translate client goals, workflows, pain points, and system constraints into clear technical architecture.
• Design how PRESHos fits into a client’s current technology stack, permissions, systems of record, data flows, and operational processes.
• Identify dependencies, risks, integration requirements, and implementation paths before work begins.
• Support proposals, demos, statements of work, and solution narratives with credible technical direction.
• Help determine what should be built, what should be validated first, and what should not be built.
• Design AI-enabled systems across agents, tools, integrations, workflow orchestration, RAG, voice interfaces, observability, and governance.
• Define tool-calling patterns, prompt architecture, data access patterns, error handling, escalation paths, and human-in-the-loop workflows.
• Build reference architectures and reusable patterns that improve speed and consistency across client implementations.
• Make technology recommendations based on client fit, implementation speed, security, maintainability, and integration requirements.
• Stay current on AI-native development tools, LLM APIs, agent frameworks, MCP tooling, workflow systems, and developer infrastructure.
• Ensure client-facing technical work is ready for real implementation, not just a working demo.
• Prepare architecture documentation, handoff notes, dependency documentation, and implementation guidance.
• Confirm that configuration, environment variables, credential handling, and deployment requirements are clearly defined.
• Review core logic, integration points, source code quality, known limitations, and support requirements before client handoff.
• Ensure deliverables are understandable, testable, configurable, secure, and practical for client technical teams to adopt.
• Guide Forward Deployed Engineers across active client workstreams.
• Set technical direction and help engineers make practical architecture and integration decisions.
• Review code and technical approaches for quality, maintainability, and client fit.
• Pair with engineers on complex architecture, integration, and AI system design problems.
• Help unblock implementation work quickly without sacrificing long-term maintainability.
• Build reusable internal delivery patterns, technical documentation, and implementation playbooks.
• Work directly with client engineering, IT, operations, and business stakeholders during implementation.
• Support integration planning without requiring direct access to client production credentials.
• Help resolve integration questions, clarify architecture decisions, and support knowledge transfer.
• Participate in sprint planning, demos, feedback sessions, and executive technical reviews as needed.
• Represent PRESHai’s technical approach clearly and confidently in client-facing conversations.
• Use AI-native development tools as part of the daily delivery workflow.
• Work comfortably with tools such as Claude Code, Cursor, Codex, LLM APIs, AI-assisted testing, and AI-assisted documentation.
• Use AI tools to accelerate development, documentation, testing, research, and implementation planning.
• Evaluate emerging tools and turn effective approaches into repeatable PRESHai delivery patterns.
Qualifications:
Required:
• 5+ years of experience designing, building, and shipping production software systems.
• Hands-on experience building LLM-powered, AI-enabled, automation, integration, or workflow systems in production environments.
• Strong production coding ability in TypeScript and/or Python.
• Practical experience with APIs, databases, OAuth flows, third-party integrations, webhooks, and system-to-system data movement.
• Experience with LLM application patterns, including tool/function calling, RAG, prompt architecture, structured outputs, evals, and workflow automation.
• Strong integration experience across systems you did not choose, such as CRM, PSA, ITSM, ERP, communication platforms, databases, and custom internal systems.
• Fluency in at least one major cloud ecosystem, such as Azure and Microsoft 365, AWS, or GCP.
• Experience with PostgreSQL, API design, event-driven systems, durable workflow patterns, and production observability.
• Ability to lead technical discovery with senior client stakeholders.
• Ability to review code, set technical direction, and guide other engineers.
• Strong written and verbal communication skills.
• Comfort operating in a fast-moving environment with multiple active client workstreams.
Preferred:
• Experience building agentic AI systems, tool-calling systems, MCP servers, or multi-step AI workflows.
• Experience implementing AI, automation, or integration systems in MSP, VAR, distributor, vendor, professional services, legal, or complex B2B environments.
• Microsoft 365 and Azure experience, including Graph API, Teams, Entra ID, and Bot Service.
• Production voice AI experience using Twilio, ElevenLabs, OpenAI Realtime API, or similar platforms.
• Experience with MCP servers and tool-based agent architecture.
• Experience with Inngest, Temporal, or comparable workflow orchestration platforms.
• Experience in consulting, agency, implementation, or professional services environments.
• Experience designing systems that other engineers had to build, operate, or integrate.
• Experience working directly with client technical teams during implementation or handoff.
Company:
PRESHai helps IT channel organizations implement AI systems that improve operations, accelerate execution, and create measurable business value. Founded in 2015, the company is headquartered in Tampa, USA, with a team of 11-50 employees. The company is currently Early Stage.