AI Platform Engineer

Corebridge Financial is a financial services company that partners with financial professionals and institutions to help people take action in their financial lives. The AI Platform Engineer will design, build, and operate secure, scalable, and reliable enterprise AI/ML platform capabilities on AWS, supporting generative AI, machine learning, and agentic AI workloads. The role also involves automation, data integration, security and governance, reliability, collaboration, and evaluation of emerging technologies.

What you'll do:

• AI/ML Platform Engineering: Build and enhance reusable platform services, development patterns, and automation that support AI/ML model development, deployment, inference, and lifecycle management on AWS
• AWS Engineering: Develop and support cloud-native solutions using relevant AWS services for compute, storage, networking, security, observability, data processing, and AI/ML, including Amazon Bedrock and Amazon SageMaker where applicable
• Generative and Agentic AI Enablement: Support the development and integration of generative AI applications, AI agents, APIs, model endpoints, prompt workflows, and retrieval-augmented generation solutions
• Platform Automation: Create infrastructure-as-code, CI/CD pipelines, deployment templates, configuration standards, and self-service capabilities that improve engineering productivity and consistency
• Data and Integration: Help connect AI/ML workloads to enterprise data platforms, APIs, event streams, and data pipelines while applying appropriate access controls and data-handling standards
• Security and Governance: Implement platform controls for identity and access management, secrets protection, encryption, logging, monitoring, auditability, model governance, and responsible AI practices
• Reliability and Operations: Build monitoring, alerting, troubleshooting, cost-management, and operational support capabilities for AI/ML services and production workloads
• Collaboration: Partner with data scientists, software engineers, data engineers, architects, security teams, and business stakeholders to translate use-case needs into scalable platform solutions
• Continuous Learning: Evaluate emerging AI/ML and AWS technologies through prototypes and proofs of concept, document findings, and contribute to platform standards and reusable engineering guidance

What they're looking for:

• • Bachelor's or master's degree in Computer Science, Data Science, Engineering, Information Systems, or a related technical field. Recent graduates are encouraged to apply
• • For new graduates, relevant internships, co-op assignments, research, capstone projects, or substantial hands-on coursework in AWS, AI/ML, data science, or software engineering will be considered
• • Foundational experience with AWS technologies and cloud concepts, including identity and access management, networking, compute, storage, security, and monitoring
• • Hands-on exposure to AI/ML concepts and tools, 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, along with working knowledge of SQL, APIs, version control, and automated testing
• • Exposure to infrastructure-as-code and CI/CD tools, such as AWS CloudFormation, Terraform, AWS CDK, GitHub Actions, or comparable technologies, is beneficial
• • Understanding of secure engineering practices, data privacy, responsible AI, logging, monitoring, and operational reliability
• • Strong problem-solving, communication, and collaboration skills, with a willingness to learn and work across multidisciplinary teams
• • AWS certification, AI/ML coursework, cloud labs, hackathons, open-source contributions, or a portfolio demonstrating practical engineering work
• • Exposure to Amazon Bedrock, Amazon SageMaker, container technologies, serverless services, vector databases, orchestration frameworks, or observability tools
• • Experience in financial services or another regulated industry is helpful but not required
• This position is based in Corebridge Financial's Houston, TX office and is subject to our hybrid working policy, which gives colleagues the benefits of working both in an office and remotely

Benefits:

• Hybrid working policy, with the benefits of working both in an office and remotely.
• Medical, dental and vision insurance plans.
• Mental health support and wellness initiatives.
• In the U.S., a 401(k) Plan with a dollar-for-dollar Company matching contribution of up to 6% of eligible pay and a Company contribution equal to 3% of eligible pay, subject to annual IRS limits and Plan terms; these Company contributions vest immediately.
• Confidential counseling services and resources available to all employees through the Employee Assistance Program.
• Matching charitable donations 1:1, up to $5,000, to tax-exempt organizations.
• Up to 16 volunteer hours annually through Volunteer Time Off.
• Eligible employees start with at least 24 Paid Time Off (PTO) days.