AI Platform Engineer
Corebridge Financial22 hours ago
Houston, TX, USAEntry Level / Mid Level
Responsibilities
- Build reusable AI/ML platform services, development patterns, automation, and lifecycle capabilities on AWS.
- Develop cloud-native solutions using AWS services for compute, storage, networking, security, observability, data processing, and AI/ML.
- Enable 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 engineering capabilities.
- Connect AI/ML workloads to enterprise data platforms, APIs, event streams, and data pipelines while applying access and data-handling controls.
- Implement identity and access management, secrets protection, encryption, logging, monitoring, auditability, model governance, and responsible AI controls.
- Build monitoring, alerting, troubleshooting, cost-management, and operational support capabilities for AI/ML production workloads.
- Collaborate with data scientists, software engineers, data engineers, architects, security teams, and business stakeholders.
- Evaluate emerging AI/ML and AWS technologies through prototypes and proofs of concept and contribute to platform standards.
Requirements
- Bachelor's or master's degree in Computer Science, Data Science, Engineering, Information Systems, or a related technical field.
- Experienced candidates should preferably have 2+ years of relevant experience in cloud engineering, software engineering, data engineering, MLOps, AI/ML engineering, or platform engineering.
- New graduates may qualify through relevant internships, co-op assignments, research, capstone projects, or substantial hands-on coursework.
- Foundational experience with AWS 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, 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, or GitHub Actions is beneficial.
- Understanding of secure engineering, data privacy, responsible AI, logging, monitoring, and operational reliability.
- Preferred qualifications include AWS certification, AI/ML coursework, cloud labs, hackathons, open-source contributions, or a practical engineering portfolio.
- Exposure to Amazon Bedrock, Amazon SageMaker, container technologies, serverless services, vector databases, orchestration frameworks, or observability tools is preferred.
- Financial services or other regulated-industry experience is helpful but not required.
Benefits
- Hybrid work arrangement combining the Houston, Texas office and remote work.
- Medical, dental, vision, mental health, and wellness benefits.
- U.S. 401(k) benefits with dollar-for-dollar company matching up to 6% of eligible pay and an additional 3% company contribution, subject to plan terms.
- Employee Assistance Program with confidential counseling and support resources.
- Matching charitable donations at a 1:1 rate up to $5,000.
- Up to 16 hours of annual Volunteer Time Off.
- At least 24 Paid Time Off days for eligible employees.
- Estimated travel may be up to 25%; relocation is not provided.