AI Platform Engineer

Location: Houston, Texas, United States; hybrid work from the Houston office and remotely. Travel may include up to 25%.

Company

hirify.global provides financial products and services for financial professionals and institutions.

What you will do

• Build and operate reusable AI/ML platform services for model development, deployment, inference, and lifecycle management on AWS.
• Develop cloud-native solutions using AWS services including compute, storage, networking, security, observability, data processing, Amazon Bedrock, and Amazon SageMaker.
• Enable generative AI and agentic AI applications, APIs, model endpoints, prompt workflows, and retrieval-augmented generation solutions.
• Create infrastructure-as-code, CI/CD pipelines, deployment templates, configuration standards, and self-service engineering capabilities.
• Connect AI/ML workloads to enterprise data platforms, APIs, event streams, and data pipelines while applying access controls and data-handling standards.
• Implement security, governance, monitoring, alerting, troubleshooting, cost management, and operational support for production AI/ML services.

Requirements

• Bachelor’s or master’s degree in computer science, data science, engineering, information systems, or a related technical field.
• Experienced candidates should have 2+ years of relevant experience in cloud, software, data, MLOps, AI/ML, or platform engineering; recent graduates may qualify through internships, research, capstone projects, or substantial coursework.
• Foundational experience with AWS, including identity and access management, networking, compute, storage, security, and monitoring.
• Hands-on exposure to AI/ML concepts such as model training or inference, generative AI, large language models, embeddings, vector search, prompt engineering, or MLOps.
• Programming ability in Python, Java, or a similar language, plus working knowledge of SQL, APIs, version control, and automated testing.
• Understanding of secure engineering, data privacy, responsible AI, logging, monitoring, and operational reliability.

Nice to have

• AWS certification, AI/ML coursework, cloud labs, hackathons, open-source contributions, or a practical engineering portfolio.
• Exposure to Amazon Bedrock, Amazon SageMaker, containers, serverless services, vector databases, orchestration frameworks, or observability tools.
• Experience in financial services or another regulated industry.

Culture & Benefits

• Collaborative environment across IT, data, engineering, architecture, security, and business teams.
• Hybrid work combining office and remote work.
• Medical, dental, vision, mental health, and wellness benefits.
• U.S. 401(k) matching of up to 6% of eligible pay plus a company contribution of 3%, subject to plan terms and limits.
• At least 24 paid time-off days for eligible employees, employee assistance resources, charitable donation matching, and volunteer time off.