AI Data Engineer Visa Sponsorship Jobs in Florida
Florida's growing tech sector, anchored by Miami's emerging AI hub, Tampa's financial technology firms, and Orlando's simulation and defense industry, is generating steady demand for AI data engineers. Major employers including Chewy, Carnival Corporation, and University of Florida Health sponsor H-1B visa and other work visas for qualified candidates in this role.
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Who we are:
Shape a brighter financial future with us.
Together with our members, we're changing the way people think about and interact with personal finance.
We're a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we're at the forefront. We're proud to come to work every day knowing that what we do has a direct impact on people's lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The role:
We are seeking a Staff Risk AI & Data Engineer to lead a high-performing engineering pod and drive technical excellence, operational maturity, and AI-enabled engineering practices across the broader Risk Data organization.
This is a senior technical leadership role focused on scaling modern data platforms, AI-native engineering workflows, and organizational standards across multiple teams. You will lead through technical strategy, process optimization, team development, and scalable framework creation while partnering closely with engineering leadership, product, compliance, infrastructure, analytics, and external vendors.
The ideal candidate combines strong leadership and team calibration experience with deep expertise across Snowflake, dbt, Python, Airflow, and modern AI-enabled engineering workflows. This role requires a hands-on technical leader who can challenge architectural decisions, improve operational efficiency, and help shape the long-term direction of SoFi's Risk Data ecosystem.
What you'll do:
Lead, mentor, calibrate, and upskill a high-performing pod of data engineers while raising the technical and operational bar across the broader Risk Data organization.
Conduct regular skills assessments, identify development gaps, and create targeted growth plans to strengthen engineering capabilities and support long-term succession planning.
Establish measurable ownership frameworks, delivery KPIs, and operational standards that improve accountability, scalability, and engineering quality.
Champion AI-native engineering workflows across the organization, including AI-assisted development environments, intelligent alerting and triage systems, automated documentation, and AI-powered operational tooling.
Standardize and optimize engineering and data delivery processes across multiple teams to improve predictability, scalability, and delivery efficiency.
Design and implement scalable frameworks, templates, and standards across onboarding, incident response, semantic layers, dbt modeling, observability, governance, and data validation practices.
Provide technical leadership across Snowflake platform architecture, dbt transformation strategy, Airflow orchestration, AI-enabled workflows, and enterprise-scale data platform governance.
Review and challenge technical strategies, pipeline architectures, and implementation plans to ensure long-term scalability, reliability, compliance, and operational maturity.
Ensure strong governance, security, lineage, observability, and compliance standards across production data systems and AI-enabled workflows.
Serve as the primary technical liaison for strategic vendor and platform relationships, including Snowflake, credit bureau providers, governance tooling vendors, and AI/data platform partners.
Partner with vendors on platform optimization, feature adoption, integration strategy, SLA management, and operational scalability initiatives.
Collaborate closely with platform engineering, infrastructure, compliance, analytics, and model risk teams to align Risk Data initiatives with broader enterprise strategy.
Evaluate emerging AI and data technologies, including AI-powered ETL, intelligent monitoring systems, and LLM-enabled operational tooling, and make strategic build-versus-buy recommendations.
Partner with Product Managers and cross-functional stakeholders to translate complex business and Risk requirements into scalable engineering roadmaps and technical solutions.
Clearly communicate operational health, delivery metrics, technical risks, and engineering strategy to technical and non-technical leadership stakeholders.
What you'll need:
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
8+ years of experience in data engineering, platform engineering, or enterprise-scale data infrastructure environments.
3+ years of experience leading engineering teams, technical pods, or cross-functional technical initiatives.
Deep hands-on expertise with Snowflake, including platform architecture, optimization, governance, performance tuning, and enterprise-scale data platform management.
Strong experience with dbt, including transformation frameworks, semantic layer strategy, testing, and scalable data modeling practices.
Strong programming experience with Python, SQL, and modern data engineering patterns.
Experience with Apache Airflow and production-grade orchestration workflows.
Demonstrated experience leveraging AI tools and AI-assisted workflows to improve engineering productivity, operational efficiency, monitoring, documentation, or incident response.
Strong understanding of governance, observability, compliance, lineage, and access-control best practices across enterprise data environments.
Proven ability to mentor engineers, influence technical direction, drive organizational standards, and scale engineering excellence across teams.
Strong communication and stakeholder management skills with experience partnering across engineering, product, compliance, infrastructure, analytics, and vendor organizations.
Nice to have:
Experience within financial services, fintech, lending, or risk management environments.
Familiarity with RAG systems, intelligent agents, or LLM-powered operational tooling.
Experience implementing AI-assisted SDLC or AI-native engineering workflows at scale.
Experience with enterprise governance, lineage, or observability tooling.
Experience managing strategic vendor or platform partnerships.
Familiarity with CI/CD, cloud-native infrastructure, and distributed systems architecture.
Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate's experience, skills, and location.
To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
Internal Employees
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.
Employee Applicant Privacy Notice
Who we are:
Shape a brighter financial future with us.
Together with our members, we're changing the way people think about and interact with personal finance.
We're a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we're at the forefront. We're proud to come to work every day knowing that what we do has a direct impact on people's lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The role:
We are seeking a Staff Risk AI & Data Engineer to lead a high-performing engineering pod and drive technical excellence, operational maturity, and AI-enabled engineering practices across the broader Risk Data organization.
This is a senior technical leadership role focused on scaling modern data platforms, AI-native engineering workflows, and organizational standards across multiple teams. You will lead through technical strategy, process optimization, team development, and scalable framework creation while partnering closely with engineering leadership, product, compliance, infrastructure, analytics, and external vendors.
The ideal candidate combines strong leadership and team calibration experience with deep expertise across Snowflake, dbt, Python, Airflow, and modern AI-enabled engineering workflows. This role requires a hands-on technical leader who can challenge architectural decisions, improve operational efficiency, and help shape the long-term direction of SoFi's Risk Data ecosystem.
What you'll do:
Lead, mentor, calibrate, and upskill a high-performing pod of data engineers while raising the technical and operational bar across the broader Risk Data organization.
Conduct regular skills assessments, identify development gaps, and create targeted growth plans to strengthen engineering capabilities and support long-term succession planning.
Establish measurable ownership frameworks, delivery KPIs, and operational standards that improve accountability, scalability, and engineering quality.
Champion AI-native engineering workflows across the organization, including AI-assisted development environments, intelligent alerting and triage systems, automated documentation, and AI-powered operational tooling.
Standardize and optimize engineering and data delivery processes across multiple teams to improve predictability, scalability, and delivery efficiency.
Design and implement scalable frameworks, templates, and standards across onboarding, incident response, semantic layers, dbt modeling, observability, governance, and data validation practices.
Provide technical leadership across Snowflake platform architecture, dbt transformation strategy, Airflow orchestration, AI-enabled workflows, and enterprise-scale data platform governance.
Review and challenge technical strategies, pipeline architectures, and implementation plans to ensure long-term scalability, reliability, compliance, and operational maturity.
Ensure strong governance, security, lineage, observability, and compliance standards across production data systems and AI-enabled workflows.
Serve as the primary technical liaison for strategic vendor and platform relationships, including Snowflake, credit bureau providers, governance tooling vendors, and AI/data platform partners.
Partner with vendors on platform optimization, feature adoption, integration strategy, SLA management, and operational scalability initiatives.
Collaborate closely with platform engineering, infrastructure, compliance, analytics, and model risk teams to align Risk Data initiatives with broader enterprise strategy.
Evaluate emerging AI and data technologies, including AI-powered ETL, intelligent monitoring systems, and LLM-enabled operational tooling, and make strategic build-versus-buy recommendations.
Partner with Product Managers and cross-functional stakeholders to translate complex business and Risk requirements into scalable engineering roadmaps and technical solutions.
Clearly communicate operational health, delivery metrics, technical risks, and engineering strategy to technical and non-technical leadership stakeholders.
What you'll need:
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
8+ years of experience in data engineering, platform engineering, or enterprise-scale data infrastructure environments.
3+ years of experience leading engineering teams, technical pods, or cross-functional technical initiatives.
Deep hands-on expertise with Snowflake, including platform architecture, optimization, governance, performance tuning, and enterprise-scale data platform management.
Strong experience with dbt, including transformation frameworks, semantic layer strategy, testing, and scalable data modeling practices.
Strong programming experience with Python, SQL, and modern data engineering patterns.
Experience with Apache Airflow and production-grade orchestration workflows.
Demonstrated experience leveraging AI tools and AI-assisted workflows to improve engineering productivity, operational efficiency, monitoring, documentation, or incident response.
Strong understanding of governance, observability, compliance, lineage, and access-control best practices across enterprise data environments.
Proven ability to mentor engineers, influence technical direction, drive organizational standards, and scale engineering excellence across teams.
Strong communication and stakeholder management skills with experience partnering across engineering, product, compliance, infrastructure, analytics, and vendor organizations.
Nice to have:
Experience within financial services, fintech, lending, or risk management environments.
Familiarity with RAG systems, intelligent agents, or LLM-powered operational tooling.
Experience implementing AI-assisted SDLC or AI-native engineering workflows at scale.
Experience with enterprise governance, lineage, or observability tooling.
Experience managing strategic vendor or platform partnerships.
Familiarity with CI/CD, cloud-native infrastructure, and distributed systems architecture.
Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate's experience, skills, and location.
To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
Internal Employees
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.
AI Data Engineer Job Roles in Florida
See all 70+ AI Data Engineer Jobs in Florida
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Search AI Data Engineer Jobs in FloridaAI Data Engineer Jobs in Florida: Frequently Asked Questions
Which companies in Florida sponsor visas for AI data engineers?
Florida-based employers with documented H-1B sponsorship history in data and AI roles include Chewy, Carnival Corporation, NextEra Energy, AdventHealth, and Citrix. Miami-headquartered tech firms and defense contractors in the Orlando corridor such as Lockheed Martin and L3Harris also regularly sponsor foreign nationals for AI and data engineering positions. University systems including the University of Florida and University of Miami sponsor roles through academic and research appointments as well.
Which visa types are most common for AI data engineer roles in Florida?
The H-1B is the most common visa for AI data engineers in Florida, as the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, data science, or a related field. Candidates with advanced degrees may also be sponsored for O-1A visas if they have demonstrated exceptional ability. TN visas are available to Canadian and Mexican nationals working in qualifying engineering or computer-related occupations.
Which cities in Florida have the most AI data engineer sponsorship jobs?
Miami leads Florida for AI data engineer sponsorship activity, driven by its expanding tech startup ecosystem and the presence of regional headquarters for financial services and logistics firms. Tampa and St. Petersburg follow closely, with strong demand from fintech companies and healthcare networks. Orlando contributes sponsorship opportunities through its defense, simulation, and hospitality technology sectors. Jacksonville has a smaller but growing presence through banking and insurance employers.
How to find ai data engineer visa sponsorship jobs in Florida?
Migrate Mate is built specifically for international candidates seeking visa sponsorship and lets you filter AI data engineer roles by state, so you can view Florida-specific openings from employers that have a history of sponsoring work visas. Rather than sorting through general job listings with no indication of sponsorship intent, Migrate Mate surfaces roles where sponsorship is confirmed or highly likely, which is particularly useful in a competitive market like South Florida or Tampa Bay.
Are there any Florida-specific factors AI data engineers should know about when seeking sponsorship?
Florida has no state income tax, which affects prevailing wage calculations and how employers structure compensation packages relative to Department of Labor wage levels. The state's concentration of healthcare, hospitality, defense, and financial services industries means AI data engineer roles often require domain-specific experience in those sectors. Florida also has a strong international student pipeline through the University of Florida, Florida International University, and the University of Central Florida, creating active OPT-to-H-1B sponsorship pathways at many in-state employers.
What is the prevailing wage for sponsored ai data engineer jobs in Florida?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.