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Ai Solutions Architect Jobs in Boca Raton, FL (NOW HIRING)

Kforce Technology Staffing

AI Solution Architect

Davie, FL · On-site

$57.75 - $76/hr

Partner with engineering, data, security, and business teams to deliver enterprise AI solutions * Present architectural recommendations and technology roadmaps to executive stakeholders * Mentor ...

Humana

Lead Solutions Architect

Fort Lauderdale, FL · On-site

As Lead Solution Architect, you'll be the senior individual contributor on a team with broad ... Proven ability to integrate AI systems with event-driven microservices, vector databases/feature ...

Humana

Lead Solutions Architect

Fort Lauderdale, FL · On-site

As Lead Solution Architect, you'll be the senior individual contributor on a team with broad ... Proven ability to integrate AI systems with event-driven microservices, vector databases/feature ...

Humana

Lead Solutions Architect

Fort Lauderdale, FL · On-site

As Lead Solution Architect, you'll be the senior individual contributor on a team with broad ... Proven ability to integrate AI systems with event-driven microservices, vector databases/feature ...

Eisneramper Llp

AI Solution Architect

Fort Lauderdale, FL · On-site +1

$60.25 - $79.25/hr

... solutions across tax, audit, outsourcing and advisory services. This role is essential to ... in AI/ML architecture role * 3+ years of hands-on experience with Azure cloud services and ...

Td

Solutions Architect (US)

Fort Lauderdale, FL · On-site

$79K - $127K/yr

Technology Solutions The Solutions Architect (IT Solutions Designer) leads the creation of a ... Experience leveraging Artificial Intelligence (AI) and Generative AI tools to improve solution ...

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All JobsAi Solutions Architect JobsAi Solutions Architect Jobs in Boca Raton, FL

Ai Solutions Architect information

See Boca Raton, FL salary details

$15

$66

$90

How much do ai solutions architect jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for ai solutions architect in Boca Raton, FL is $66.39, according to ZipRecruiter salary data. Most workers in this role earn between $57.31 and $75.53 per hour, depending on experience, location, and employer.

What is an AI Solutions Architect?

AI Solutions Architects are professionals who design, develop, and implement artificial intelligence solutions to solve business problems. They work closely with stakeholders to understand requirements, select appropriate AI technologies, and ensure that systems are scalable, secure, and aligned with organizational goals. Their responsibilities often include overseeing the integration of AI models into existing infrastructures, collaborating with data scientists and engineers, and guiding the end-to-end lifecycle of AI projects. They also stay updated on the latest AI advancements to recommend innovative solutions. Overall, AI Solutions Architects bridge the gap between technical teams and business objectives to drive successful AI adoption.

What skills and qualifications are needed to be an AI Solutions Architect?

To thrive as an AI Solutions Architect, you need expertise in machine learning, data science, and software engineering, typically supported by a degree in computer science or a related field. Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud), AI/ML frameworks (like TensorFlow or PyTorch), and relevant certifications are highly valued. Strong problem-solving, stakeholder communication, and project management skills set top performers apart. These competencies ensure effective design, deployment, and integration of AI solutions that align with business objectives.

How does an AI Solutions Architect collaborate with cross-functional teams during a project lifecycle?

AI Solutions Architects play a central role in bridging the gap between technical teams, such as data scientists and engineers, and non-technical stakeholders like business analysts and project managers. They are responsible for gathering requirements, designing scalable AI solutions, and ensuring alignment with business objectives throughout the project. Regular collaboration involves facilitating meetings, providing technical guidance, and translating complex AI concepts into actionable plans for all team members. This collaborative approach ensures that projects are delivered efficiently and meet both technical and business needs.

What is the difference between Ai Solutions Architect vs Data Scientist?

AspectAi Solutions ArchitectData Scientist
Required CredentialsBachelor's or higher in CS, AI, or related fields; certifications in cloud platforms or AI toolsBachelor's or higher in CS, Statistics, or related fields; certifications in data analysis or machine learning
Work EnvironmentDesigning AI solutions, collaborating with engineering teams, implementing AI models in productionAnalyzing data, building models, interpreting results to inform business decisions
Employer & Industry UsageTech companies, AI-focused firms, large enterprises integrating AI solutionsResearch institutions, tech companies, finance, healthcare, and marketing sectors

While both roles involve AI and data, an Ai Solutions Architect focuses on designing and deploying AI systems within organizations, whereas a Data Scientist primarily analyzes data and develops models to extract insights. The architect role emphasizes solution architecture and implementation, often requiring knowledge of cloud platforms and engineering, while the Data Scientist concentrates on statistical analysis and model development.

How much does an AI Solutions Architect make?

An AI Solutions Architect typically earns between $100,000 and $160,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and cloud platforms can earn higher salaries, often exceeding $180,000.

What does an AI Solutions Architect do?

An AI Solutions Architect designs and implements artificial intelligence solutions to meet business needs, often working with machine learning models, data pipelines, and cloud platforms. They analyze requirements, develop technical strategies, and collaborate with teams to deploy scalable AI systems, typically requiring knowledge of programming, data science, and AI tools. Their role ensures AI technologies are effectively integrated into organizational processes.

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For Ai Solutions Architect jobs in Boca Raton, FL, the most frequently searched job titles are:

What job categories do people searching Ai Solutions Architect jobs in Boca Raton, FL look for?

The top searched job categories for Ai Solutions Architect jobs in Boca Raton, FL are:

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Cities near Boca Raton, FL with the most Ai Solutions Architect job openings:

Ai Solutions Architect jobs near you
Infographic showing various Ai Solutions Architect job openings in Boca Raton, FL as of August 2026, with employment types broken down into 83% Full Time, 12% Part Time, and 5% Contract. Highlights an 73% Physical, 3% Hybrid, and 24% Remote job distribution, with an average salary of $138,097 per year, or $66.4 per hour.

AI Solutions Architect (Agentic AI)

OZ Digital LLC

Boca Raton, FL • On-site

$59.75 - $78.75/hr

Full-time

Medical, Retirement, PTO

Posted 6 days ago

Job description

AI Solutions Architect (Agentic AI)
We believe work should be innately rewarding and a team-building venture. Working with our teammates and clients should be an enjoyable journey where we can learn, grow as professionals, and achieve amazing results. Our core values revolve around this philosophy. We are relentlessly committed to helping our clients achieve their business goals, leapfrog the competition, and become leaders in their industry. What drives us forward is the culture of creativity combined with a disciplined approach, passion for learning & innovation, and a 'can-do' attitude!
What We're Looking For:
We're seeking a strategic and hands-on AI Solutions Architect who can define and lead the architecture of enterprise-scale Agentic AI solutions. The ideal candidate combines deep technical expertise in generative AI, cloud platforms, enterprise architecture, and AI governance with the ability to influence business and technology leaders. You are passionate about turning emerging AI capabilities into secure, scalable, and high-value business outcomes while establishing the standards, guardrails, and architectural patterns that enable multiple teams to successfully deliver AI-powered solutions.
Position Overview:
As an AI Solutions Architect (Agentic AI), you will partner with Architecture and Engineering leadership to shape the organization's AI strategy, reference architectures, and technology roadmap. You will be responsible for designing enterprise AI platforms, agentic AI frameworks, RAG architectures, governance standards, security controls, and integration patterns that support scalable and responsible AI adoption. This role requires evaluating emerging technologies, guiding build-versus-buy decisions, establishing engineering best practices, and collaborating across business, security, data, and technology teams to deliver innovative AI solutions that drive measurable business value.
Key Responsibilities:
  • Shape the AI strategy and roadmap: Align AI capabilities and investments with business priorities, while honestly assessing data, technology, and organizational readiness and sequencing initiatives for the greatest impact.
  • Define the architecture for agentic AI: Establish enterprise reference architectures for different agent patterns, including supervisor/worker, peer-to-peer, sequential workflows, and provide clear guidance on when to use each approach.
  • Architect the AI knowledge and memory layer: Design how AI solutions manage session context, long-term knowledge, vector stores, knowledge graphs, and audit or episodic memory so information can be retrieved consistently and reliably.
  • Establish enterprise RAG patterns: Define standards for retrieval-augmented generation, caching, embeddings, vector search, reranking, data lineage, observability, and evaluation so teams can build solutions consistently and at scale.
  • Set standards for AI tools and agent interfaces: Define patterns for APIs, MCP servers, agent tools, and inter-agent communication so capabilities can be securely reused across applications and delivery teams.
  • Lead build-versus-buy decisions: Evaluate models, platforms, and vendors based on business value, capability, cost, scalability, flexibility, and long-term risk, including decisions around multi-model strategies, the use of both frontier and smaller language models.
  • Help determine where AI belongs: Challenge whether a problem truly needs an agent, should use a deterministic workflow, or should not be automated. Make these decisions based on business value, risk, complexity, and measurable outcomes.
  • Establish GenAIOps and engineering standards: Define enterprise practices for AI development, CI/CD, infrastructure, deployment, monitoring, and observability, including metrics such as latency, token consumption, decision traces, hallucination rates, and cost per outcome.
  • Architect enterprise AI guardrails: Establish patterns for reducing hallucinations, protecting against prompt injection, safeguarding PII, preventing data loss, detecting bias, and controlling model outputs.
  • Design secure agent identity and authorization: Define how agents authenticate and operate with least-privilege access, secure credentials, tenant isolation, row- and column-level permissions, and protection against privilege escalation across chained tool calls.
  • Drive responsible AI governance: Apply frameworks such as NIST AI RMF, ISO/IEC 42001, and OWASP LLM Top 10 while partnering with Security, Legal, Data Governance, and Compliance teams on data classification, auditability, residency, and regulatory requirements.
  • Architect enterprise integrations: Define scalable integration patterns between AI and enterprise platforms such as identity, collaboration, loyalty, CRM, CDP, ERP, and data Lakehouse.
  • Partner across business, product, and technology teams: Work with business leaders, product teams, engineering, security, data, and infrastructure teams to develop solutions that balance reusability, maintainability, integration, cost, technical debt, scalability, and security.
  • Advise senior and executive stakeholders: Translate complex AI opportunities and architectural trade-offs into clear recommendations, solution proposals, roadmaps, and architecture decisions that enable informed business decisions.

What You're Looking For:
If you're looking for an opportunity to work in a fast-growing market, surrounded by talented, motivated, and global colleagues who thrive on helping clients meet their most pressing business goals, we are the company for you. If you're driven, passionate, and want to be a 'key player' in a company's growth, we invite you to make a difference with a company that's defined by its employees. We want you to be bold, take risks, and imagine a better way to work. We should talk if we just described you!
About Us:
With more than 25 years of experience, OZ's trusted, deep expertise in Azure Cloud Solutions, Power Apps Application Development, Intelligent Automation, Enterprise Application Integration, Azure Data Strategy, and Artificial Intelligence ensures clients get rapid, effective results.
OZ is dedicated to creating a seamless blend between work and life, offering our team the flexibility to work hybrid and/or remotely. We provide competitive pay and a well-rounded benefits package, including full health coverage, a 401K, and unlimited PTO. Our culture is built on collaboration, growth, and balance - you'll have the tools and support you need to thrive. Join a team that truly lives its values and invests in your success.
Requirements
  • 8-10+ yrs. experience in software engineering and architecting enterprise solutions, including production systems you personally helped build
  • Architectural depth in one major cloud provider (Azure, AWS, or GCP) with hands-on familiarity in at least one other
  • Demonstrated experience architecting generative AI solutions on an enterprise platform - Azure OpenAI / AI Foundry, AWS Bedrock or Google Vertex AI
  • Proven design of complex RAG pipelines, including their evaluation and observability
  • Experience designing agentic or multi-agent systems: task decomposition, tool use, state and memory, guardrails and fallbacks
  • Hands-on experience with at least one orchestration framework (LangGraph, LangChain, Semantic Kernel, LlamaIndex or equivalent) and enough Python to prototype and review code credibly
  • Working knowledge of AI security and governance: prompt injection, data protection, responsible AI controls, and at least one formal framework (NIST AI RMF or ISO/IEC 42001)
  • Experience in DevOps, SDLC, containers, Kubernetes, microservices, event-driven and API design
  • Knowledge of architecture principles and industry-standard frameworks; data architecture and integration experience across a diverse landscape of package and custom applications
  • Experience working with customer data-pertaining systems such as loyalty systems, CRM, and CDP; understanding of different datastore types and how data flows across systems
  • Well-versed in API management to monitor security, application connections, traffic, and standardization
  • Experienced in sizing AI workloads for optimal performance, latency, and cost, with a thorough understanding of the underlying infrastructure
  • Performs work with a high degree of latitude. Handles the most complex issues. Possesses expert knowledge of subject matter. Provides leadership, coaching, and mentoring to the team
  • Excellent communication skills - able to hold a design position with senior engineers and explain the same trade-off to a non-technical executive without losing the substance
  • Bachelor's degree in math, computer science, or a related tech field and 8 or more years of experience

Preferred Qualifications:
  • Multi-cloud architectural experience across Azure, AWS, and GCP
  • Data platform depth (Databricks, Snowflake) and Lakehouse architecture
  • Model fine-tuning or instruction-tuning strategy; small-language-model and edge inference for cost efficiency
  • Agent identity and authorization design at enterprise scale
  • Delivery experience in a regulated environment, including model risk management exposure
  • Preferred certification in TOGAF, or professional-level cloud architecture certification (Azure Solutions Architect Expert, AWS Solutions Architect Professional, GCP Professional Cloud Architect)
  • Published work, patents, conference speaking, or open-source contribution in the AI space

Competencies:
  • Architectural fluency
  • Use-case selection and data readiness judgment
  • Design expertise
  • Technical expertise
  • Trade-off analysis
  • Stakeholder influence
  • Problem-solving skills

Benefits
  • Competitive Pay
  • 401K
  • Health Coverage

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