AI Platform Engineer

Corebridge Financial•Houston, TX

3d•Hybrid

About The Position

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.

Requirements

Bachelor's or master's degree in Computer Science, Data Science, Engineering, Information Systems, or a related technical field.
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.
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.

Nice To Haves

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.
Exposure to infrastructure-as-code and CI/CD tools, such as AWS CloudFormation, Terraform, AWS CDK, GitHub Actions, or comparable technologies, is beneficial.
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.

Responsibilities

Build and enhance reusable platform services, development patterns, and automation that support AI/ML model development, deployment, inference, and lifecycle management on AWS.
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.
Support the development and integration of generative AI applications, AI agents, APIs, model endpoints, prompt workflows, and retrieval-augmented generation solutions.
Create infrastructure-as-code, CI/CD pipelines, deployment templates, configuration standards, and self-service capabilities that improve engineering productivity and consistency.
Help connect AI/ML workloads to enterprise data platforms, APIs, event streams, and data pipelines while applying appropriate access controls and data-handling standards.
Implement platform controls for identity and access management, secrets protection, encryption, logging, monitoring, auditability, model governance, and responsible AI practices.
Build monitoring, alerting, troubleshooting, cost-management, and operational support capabilities for AI/ML services and production workloads.
Partner with data scientists, software engineers, data engineers, architects, security teams, and business stakeholders to translate use-case needs into scalable platform solutions.
Evaluate emerging AI/ML and AWS technologies through prototypes and proofs of concept, document findings, and contribute to platform standards and reusable engineering guidance.