AI Platform Engineer

Corebridge Financial, Inc.; Houston (TX); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work policy

Competitive benefits

Job summary

Corebridge Financial, Inc. is hiring an AI Platform Engineer in Houston to design, build, and operate a scalable AI/ML platform on AWS. You will enable secure, reliable AI workloads and collaborate with data scientists and engineers across the enterprise.

You will develop reusable platform services, automation, and CI/CD, while ensuring governance, security, and observability across production workloads. The role supports hybrid work within the Houston office and remote options where applicable.

Qualifications

• Fundamental AWS cloud concepts (IAM, networking, compute, storage).
• Experience with AI/ML concepts and pipelines.
• Strong programming and testing skills in Python or Java.
• Familiarity with APIs, data pipelines, and version control.
• Understanding of security, monitoring, and governance practices.

Responsibilities

• Design, build, and operate the enterprise AI/ML platform on AWS.
• Develop reusable platform services, automation, and CI/CD patterns.
• Support generative AI, AI agents, model endpoints, and prompt workflows.
• Connect AI workloads to data platforms with proper access controls.
• Collaborate with data scientists, engineers, and security teams.

Skills

Python

Java

SQL

APIs

CI/CD

Education

Bachelor's or Master's in CS/DS/Engineering

Tools

AWS

Amazon Bedrock

Amazon SageMaker

Terraform

GitHub Actions

Job description

## AI Platform EngineerApply: TX-Houston: Full time: Posted Today: JR2600897Who We Are At Corebridge Financial, we believe action is everything. That’s why every day we partner with financial professionals and institutions to make it possible for more people to take action in their financial lives, for today and tomorrow. We align to a set of Values that are the core pillars that define our culture and help bring our brand purpose to life:* We are stronger as one: We collaborate across the enterprise, scale what works and act decisively for our customers and partners.* We deliver on commitments: We are accountable, empower each other and go above and beyond for our stakeholders.* We learn, improve and innovate: We get better each day by challenging the status quo and equipping ourselves for the future.* We are inclusive: We embrace different perspectives, enabling our colleagues to make an impact and bring their whole selves to work.**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%.