AI Engineer at Popular, Inc. (Puerto Rico's leading bank) within its AI Office, designing, building, and maintaining enterprise AI/ML and Generative AI solutions — LLM/RAG apps, agentic workflows, copilots — with MLOps/CI-CD pipelines on Azure and AWS, under Responsible AI and financial-services compliance standards.
Compensation
Not disclosed
Location
Puerto Rico
Work setup
Hybrid
Seniority
Not specified
Employment
Not specified
Experience
Not specified
Category
Ai engineering
Posted
Skills
agentic-ai
ai
ai-enablement
analytics
api
api-gateway
automation
aws
aws-bedrock
azure
cdk
ci-cd
cissp
claude-code
cloud
cloud-native
cloud-security
cloudformation
containerization
cybersecurity
data-engineering
data-science
databricks
devops
generative-ai
lambda
langchain
llm
machine-learning
mcp
microservices
mlops
model-deployment
observability
openai
prompt-engineering
python
pytorch
rag
risk-assessment
sagemaker
scikit-learn
semantic-kernel
semantic-search
statistics
tensorflow
test-automation
vector-databases
version-control
Must have
Bachelor's degree in Computer Science, Software Engineering, Data Science, AI, or related technical field
5+ years in software engineering, ML/AI engineering, data engineering, or related
Experience designing, developing, and deploying production-grade AI/ML solutions
Experience with cloud platforms and enterprise technology environments
Experience implementing CI/CD, DevOps, MLOps, and engineering best practices
Strong proficiency in Python and software engineering best practices
Experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, Semantic Kernel
Experience with LLMs, Generative AI architectures, prompting, retrieval systems, and agent frameworks
Experience developing APIs, microservices, and cloud-native applications
Knowledge of Azure AI services, Azure Machine Learning, Azure OpenAI, containerization, cloud-native architectures
Familiarity with vector databases, knowledge retrieval platforms, model deployment frameworks, and AI monitoring tools
Understanding of information security, data privacy, access management, and cybersecurity principles
Must be authorized to work in the US; no visa sponsorship or transfer available
Nice to have
Master's degree in AI, Data Science, Computer Science, Engineering, or related
AWS AI/ML or Generative AI certification with hands-on Bedrock, SageMaker, RAG, agentic AI
Proficiency with Claude Code, Kiro, Amazon Q Developer, MCP, AWS Lambda, API Gateway, CloudFormation/CDK
Azure AI Engineer, Azure Developer, or Databricks Machine Learning certification
Security certification such as CISSP or cloud security credential
Full description
AI Engineer
The AI Engineer is responsible for designing, developing, deploying, and maintaining Artificial Intelligence (AI), Machine Learning (ML), and Generative AI solutions that drive innovation, operational efficiency, risk management, and customer experience improvements across Popular.
This position serves as a key technical contributor within Popular's AI Office and partners closely with Data & Analytics, Enterprise Architecture, Cybersecurity, Infrastructure, Software Engineering, Risk Management, Compliance, Legal, and business units to deliver secure, scalable, and compliant AI solutions. The AI Engineer is responsible for engineering enterprise-grade AI applications, implementing model lifecycle management practices, and ensuring AI solutions align with Responsible AI principles, regulatory requirements, and technology standards applicable to the financial services industry.
The role combines strong software engineering, data science, cloud architecture, and AI platform expertise to accelerate AI adoption while maintaining the highest levels of governance, security, resiliency, and operational excellence.
Key Responsibilities
AI Solution Engineering & Development
Design, develop, test, deploy, and support AI, Machine Learning, and Generative AI solutions that address strategic business objectives and operational challenges. Build scalable AI-enabled applications, APIs, intelligent assistants, virtual agents, copilots, and automation solutions. Develop and maintain reusable AI frameworks, engineering standards, and reference architectures to accelerate enterprise adoption.Translate business requirements into technical AI solution designs that meet functional, security, performance, and compliance requirements. Collaborate with business stakeholders, product owners, and technical teams to deliver production-ready AI capabilities.
Generative AI & Intelligent Automation
Design and implement Generative AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), semantic search, and enterprise knowledge management capabilities. Develop agentic AI workflows that automate and orchestrate business processes while maintaining appropriate governance and human oversight. Optimize prompt engineering, model orchestration, grounding strategies, and response quality frameworksEvaluate and integrate emerging AI technologies, platforms, and capabilities that support enterprise innovation objectives. Support development of internal AI copilots and digital workforce solutions that improve employee productivity and customer experiences.
AI Platform Engineering & MLOps
Ai Engineer at Popular, Inc. (Puerto Rico) — aijobsearch
Develop and support AI engineering platforms, model deployment frameworks, and MLOps capabilities. Build and maintain CI/CD pipelines, automated testing frameworks, model monitoring, and deployment automation for AI solutions. Implement observability, logging, telemetry, and performance monitoring across AI applications and services. Support model lifecycle management, version control, retraining, validation, and operational monitoring. Ensure AI solutions are scalable, resilient, and aligned with enterprise technology standards.
AI Risk, Governance & Responsible AI
Ensure AI solutions comply with enterprise policies, cybersecurity standards, model risk management requirements, privacy regulations, and applicable financial industry regulations. Support implementation of Responsible AI practices including fairness, transparency, explainability, accountability, and human oversight. Participate in AI governance reviews, model validation processes, architecture reviews, and risk assessments. Maintain technical documentation, model artifacts, deployment records, inventories, and audit evidence required for regulatory and internal oversight. Collaborate with Risk Management, Compliance, Legal, Information Security, and Internal Audit teams throughout the AI lifecycle.
Innovation & Continuous Improvement
Research emerging AI, machine learning, and cloud technologies to identify opportunities for business value creation. Participate in proof-of-concepts, pilot initiatives, and innovation programs sponsored by the AI Office. Provide technical guidance and mentorship to engineering and technology teams regarding AI engineering best practices. Contributes to the establishment of enterprise AI engineering standards, development methodologies, and operating procedures.
Required Qualifications
Education
Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Data Science, Artificial Intelligence, Mathematics, Statistics, or a related technical field. Master's degree in Artificial Intelligence, Data Science, Computer Science, Engineering, or related discipline preferred.
Experience
5+ years of experience in software engineering, machine learning engineering, AI engineering, data engineering, or related technology disciplines. Experience designing, developing, and deploying production-grade AI or machine learning solutions. Experience working with cloud platforms and enterprise technology environments. Experience implementing CI/CD, DevOps, MLOps, and software engineering best practices. Experience operating within highly regulated industries such as banking, financial services, insurance, healthcare, or government is preferred. Experience collaborating across technical and business teams in a matrixed environment.
Technical Skills
Strong proficiency in Python and software engineering best practices. Experience with AI and machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, Semantic Kernel, or similar technologies. Experience with Large Language Models (LLMs), Generative AI architectures, prompting techniques, retrieval systems, and agent frameworks. Experience developing APIs, microservices, and cloud-native applications. Knowledge of Azure AI services, Azure Machine Learning, Azure OpenAI, containerization technologies, and cloud-native architectures. Familiarity with vector databases, knowledge retrieval platforms, model deployment frameworks, and AI monitoring tools. Understanding of information security, data privacy, access management, and cybersecurity principles.
Core Competencies
AI and Machine Learning Engineering Software Engineering Excellence Cloud and Platform Engineering Problem Solving and Analytical Thinking Innovation and Technology Curiosity Responsible AI and Risk Awareness Collaboration and Influencing Skills Business Acumen and Customer Focus Continuous Learning and Adaptability Results Orientation and Accountability
Preferred Certifications and Tool Proficiency
AWS AI/ML or Generative AI certification, with hands-on proficiency in Amazon Bedrock, SageMaker, RAG, agentic AI, and production GenAI solutions. Demonstrated proficiency with AI engineering tools such as Claude Code, Kiro, Amazon Q Developer, MCP, AWS Lambda, API Gateway, CloudFormation/CDK, and CI/CD pipelines. Azure AI Engineer, Azure Developer, Databricks Machine Learning, or equivalent certification supporting multi-cloud AI engineering and MLOps.Security certification such as CISSP, cloud security, or equivalent credential supporting secure AI development in regulated environments.
Important: The candidate must provide evidence of academic preparation or courses related to the job posting, if necessary.
Our hybrid work model benefit applies to certain positions and is subject to changes based on the organizational needs.
Applicants must be authorized to work for any employer in the United States. This position is not open to applicants who need visa sponsorship or transfer of visa sponsorship at this time.
ABOUT US
Popular is Puerto Rico's leading financial institution and have been evolving since it was founded over a century ago. From a small bank it has developed into a large corporation that offer a wide variety of services and financial solutions to our customers, with presence in the United States, the Caribbean and Latin America.
As employees, we are dedicated to making our customers dreams come true by offering financial solutions in each stage of their life. Our extensive trajectory demonstrates the resiliency and determination of our employees to innovate, reach for the right solutions and strongly support the communities we serve; therefore, we value their diverse skills, experiences and backgrounds.
We reaffirm our commitment to always offer essential financial services and solutions for our customers and communities, including during emergency situations and/or natural disasters. Popular's employees are considered essential workers, whose role is critical in the continuity of these important services even under such circumstances. By applying to this position, you acknowledge that Popular may require your services during and immediately after any such events.
If you have a disability or need more information about requesting an accommodation, please contact us at **. This email inbox is monitored for such types of requests only. All information you provide will be kept confidential and will be used only to the extent required to provide needed exemptions or reasonable accommodations. Any other correspondence will not receive a response.
Are you ready for a rewarding career?
Popular is an Equal Opportunity Employer, including Disability/Vets Learn more about us at and keep updated with our latest job postings at .