Artificial Intelligence / Machine Learning Engineer
Jacksonville, Florida, United States of America
- Pay
- Pay not listed
- Work setting
Hybrid stated — work setting source
NOTE: 1) This position is hybrid (3 days onsite) in our FIS Office location in Jacksonville (FL). 2) Current and Future Sponsorship is not available for this position.
Read the full posting- Employment
Full-time — employment source
Position Type : Full time Type Of Hire : Experienced (relevant combo of work and education)
Read the full posting
Before you apply
- Eligibility
2) Current and Future Sponsorship is not available for this position. — eligibility source
2) Current and Future Sponsorship is not available for this position.
Read the full posting
What you’ll work on
Full postingAs an Artificial Intelligence and Machine Learning Engineer Lead, you will design and develop generative artificial intelligence and agent-based solutions across FIS.
Design and build generative artificial intelligence applications using proprietary and open-weight large language models.
Design and build generative AI applications using LLMs
Develop agent-based systems with planning, memory, tool use and oversight
Integrate AI solutions with enterprise platforms, APIs and business workflows
Build and deploy REST services using Flask or FastAPI
Evaluate model and agent performance for accuracy, reliability, grounding and safety
From the employer’s posting
As an Artificial Intelligence and Machine Learning Engineer Lead, you will design and develop generative artificial intelligence and agent-based solutions across FIS. You will build scalable applications using large language models and integrate them with enterprise platforms, application programming interfaces and workflows. You will also evaluate these systems for accuracy, reliability, safety and effective grounding.
Design and build generative artificial intelligence applications using proprietary and open-weight large language models.
Develop agent-based systems and workflows that support planning, memory, tool use, orchestration, human oversight and autonomous tasks.
Integrate artificial intelligence solutions with enterprise platforms, application programming interfaces and business workflows.
Build and deploy representational state transfer services using Flask or FastAPI.
Evaluate model, agent and system performance, including accuracy, reliability, grounding and safety.
What you’ll bring
All qualificationsCore experience
- Hands-on experience with large language models, prompting techniques, structured outputs, model routing, context management, memory management and retrieval-augmented generation.
- Strong proficiency in Python and experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras or pandas.
- Experience with vector databases, retrieval systems, cloud platforms such as Amazon Web Services, Google Cloud or Microsoft Azure, and services built with Flask or FastAPI.
- Bachelor's degree in engineering or a related field, or an equivalent combination of education, training and work experience.
Preferred experience
- Experience fine-tuning large language models, including parameter-efficient approaches such as low-rank adaptation and quantized low-rank adaptation.
- Familiarity with orchestration tools such as LangChain, LlamaIndex, AutoGen or the OpenAI Assistants application programming interface.
- Knowledge of production machine learning operations, continuous integration and delivery, monitoring, observability, security, compliance and data governance.
Qualification wording
Hands-on experience with large language models, prompting techniques, structured outputs, model routing, context management, memory management and retrieval-augmented generation.
Strong proficiency in Python and experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras or pandas.
Experience with vector databases, retrieval systems, cloud platforms such as Amazon Web Services, Google Cloud or Microsoft Azure, and services built with Flask or FastAPI.
Bachelor's degree in engineering or a related field, or an equivalent combination of education, training and work experience.
Experience fine-tuning large language models, including parameter-efficient approaches such as low-rank adaptation and quantized low-rank adaptation.
Familiarity with orchestration tools such as LangChain, LlamaIndex, AutoGen or the OpenAI Assistants application programming interface.
Knowledge of production machine learning operations, continuous integration and delivery, monitoring, observability, security, compliance and data governance.
Tools in this posting
- Python
- Azure
- FastAPI
- Flask
- Keras
- pandas
- PyTorch
- scikit-learn
- TensorFlow
- AWS
- GCP
Source — Tool mentions in context
- Hands-on experience with large language models, prompting techniques, structured outputs, model routing, context management, memory management and retrieval-augmented generation. - Strong proficiency in Python and experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras or pandas. - Experience with vector databases, retrieval systems, cloud platforms such as Amazon Web Services, Google Cloud or Microsoft Azure, and services built with Flask or FastAPI.
- Strong proficiency in Python and experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras or pandas. - Experience with vector databases, retrieval systems, cloud platforms such as Amazon Web Services, Google Cloud or Microsoft Azure, and services built with Flask or FastAPI. - Bachelor's degree in engineering or a related field, or an equivalent combination of education, training and work experience.
- Integrate artificial intelligence solutions with enterprise platforms, application programming interfaces and business workflows. - Build and deploy representational state transfer services using Flask or FastAPI. - Evaluate model, agent and system performance, including accuracy, reliability, grounding and safety.
Posting record
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- Live
- First seen by us
- Oct 15, 2026 · 7 days ago
- Recorded sightings
- 26
- Last seen by us
- Oct 22, 2026
- Reposted
- once since Oct 14, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
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Job description
Position Type :
Full timeType Of Hire :
Experienced (relevant combo of work and education)Job Description
Every day at FIS, innovators, problem solvers and changemakers work together to create technology that advances the world of finance. We embrace new ideas, challenge what's possible and empower our teams to make a lasting impact. If you're ready to help shape the future of fintech, unlock your next chapter with FIS.
NOTE:
1) This position is hybrid (3 days onsite) in our FIS Office location in Jacksonville (FL).
2) Current and Future Sponsorship is not available for this position.
About the role:
As an Artificial Intelligence and Machine Learning Engineer Lead, you will design and develop generative artificial intelligence and agent-based solutions across FIS. You will build scalable applications using large language models and integrate them with enterprise platforms, application programming interfaces and workflows. You will also evaluate these systems for accuracy, reliability, safety and effective grounding.
Your key responsibilities:
- Design and build generative artificial intelligence applications using proprietary and open-weight large language models.
- Develop agent-based systems and workflows that support planning, memory, tool use, orchestration, human oversight and autonomous tasks.
- Integrate artificial intelligence solutions with enterprise platforms, application programming interfaces and business workflows.
- Build and deploy representational state transfer services using Flask or FastAPI.
- Evaluate model, agent and system performance, including accuracy, reliability, grounding and safety.
What you bring:
Required qualifications:
- At least 10 years of overall professional experience, including at least 4 years working with artificial intelligence, generative artificial intelligence or agent-based artificial intelligence.
- Designing and building GenAI-powered applications using LLMs (open & proprietary)
- Building agent-based systems with planning, memory, tool use, and orchestration
- Implementing Agentic workflows (multi-agent, human-in-the-loop, autonomous tasks)
- Hands-on experience with large language models, prompting techniques, structured outputs, model routing, context management, memory management and retrieval-augmented generation.
- Strong proficiency in Python and experience with machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras or pandas.
- Experience with vector databases, retrieval systems, cloud platforms such as Amazon Web Services, Google Cloud or Microsoft Azure, and services built with Flask or FastAPI.
- Bachelor's degree in engineering or a related field, or an equivalent combination of education, training and work experience.
Preferred qualifications:
- Experience fine-tuning large language models, including parameter-efficient approaches such as low-rank adaptation and quantized low-rank adaptation.
- Familiarity with orchestration tools such as LangChain, LlamaIndex, AutoGen or the OpenAI Assistants application programming interface.
- Knowledge of production machine learning operations, continuous integration and delivery, monitoring, observability, security, compliance and data governance.
The impact you'll make:
The FIS artificial intelligence and machine learning team identifies, explores and implements solutions designed to support revenue growth and operational savings. The team brings together solution architects, data scientists and machine learning engineers. As an Artificial Intelligence and Machine Learning Engineer Lead, you will help turn emerging technologies into practical solutions that can be applied across the organization
What We Offer you:
At FIS, you can grow your career as far as you want to take it. Here’s what else we offer:
- Opportunities to make an impact in fintech
- Personal and professional learning
- Inclusive, diverse work environment
- Resources to give back to your community
- Competitive salary and benefits
#LI-ST1
Privacy Statement
FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.
EEOC Statement
FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here
For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.
Sourcing Model
Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.
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Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Jacksonville, Florida, United States of America
NOTE: 1) This position is hybrid (3 days onsite) in our FIS Office location in Jacksonville (FL). 2) Current and Future Sponsorship is not available for this position.
- Work authorization
1) This position is hybrid (3 days onsite) in our FIS Office location in Jacksonville (FL). 2) Current and Future Sponsorship is not available for this position. About the role:
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