Who You’ll Work With

The Information Technology organization is the technological foundation of our business and works in collaboration with our partners from across the company. The team drives technology and digital transformation, partners with business leaders to design and execute new strategies through IT and operations services and ensures the necessary IT risk management and security measures are in place and aligned with enterprise architecture standards and principles. 

About The Role

We are seeking an AI Platform Engineer to help design, build, and operate the enterprise AI/ML platform capabilities that enable secure, scalable, and reliable AI and machine learning solutions. This role will work across cloud infrastructure, data, AI  engineering, and governance to support generative AI, machine learning, and agentic AI workloads on AWS. The position is open to early-career professionals with two to three years of relevant experience as well as new graduates with strong academic foundations and relevant internship or project experience. 

Responsibilities

• 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.

Skills and Qualifications

• 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 experienced candidates, 2+ years of relevant experience in cloud engineering, software engineering, data engineering, MLOps, AI/ML engineering, or platform engineering is preferred.
• 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.

Preferred Qualifications

• 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.

Compensation:

Corebridge also offers a range of competitive benefits as part of the total compensation package, as detailed below.

Work Location

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.

Estimated Travel

May include up to 25%.

#LI-SAFG  #LI-CW1 #LI-Hybrid

Why Corebridge?

At Corebridge Financial, we prioritize the health, well-being, and work-life balance of our employees. Our comprehensive benefits and wellness program is designed to support employees both personally and professionally, ensuring that they have the resources and flexibility needed to thrive.

Benefit Offerings Include:

• Health and Wellness: We offer a range of medical, dental and vision insurance plans, as well as mental health support and wellness initiatives to promote overall well-being.
• Retirement Savings: We offer retirement benefits options, which vary by location.In the U.S., our competitive 401(k) Plan offers a generous 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.
• Employee Assistance Program: Confidential counseling services and resources are available to all employees.
• Matching charitable donations: Corebridge matches donations to tax-exempt organizations 1:1, up to $5,000.
• Volunteer Time Off: Employees may use up to 16 volunteer hours annually to support activities that enhance and serve communities where employees live and work.
• Paid Time Off: Eligible employees start off with at least 24 Paid Time Off (PTO) days so they can take time off for themselves and their families when they need it.

Eligibility for and participation in employer-sponsored benefit plans and Company programs will be subject to applicable law, governing Plan document(s) and Company policy.

Functional Area: