Platform Engineer IV - Capgemini

St. Louis, MO, United States (On-site)

Contract (4 months 1 day)

Published 5 hours ago

api development

Amazon Web Services (AWS)

CI/CD

Linux administration

Networking & Security

terraform

AI/ML

python programming

Infrastructure Intelligence and Analytics (IIA) team builds and operates the data platform and AI agent infrastructure that powers proactive network monitoring and autonomous investigation for network operations.

As part of this group, the Platform Engineer IV designs, builds, and maintains the AWS infrastructure that underpins the IIA Data Lake, agent runtime environments, CI/CD pipelines, and graph database systems, and develops the utilitarian application code, automation, and internal tooling for those systems.

This role ensures production environments are stable, scalable, and secure while enabling data science and agentic AI workloads to operate reliably at scale.

Major duties & Responsibilities:

Responsibilities span across the following areas. Individual focus areas will be determined based on team needs and candidate strengths:

Infrastructure and Data Lake:

Design and manage AWS infrastructure for the IIA Data Lake including S3 storage, Glue data catalog, Athena query engine, and EMR compute clusters.

Manage cross-account connectivity, VPC networking, security groups, and IAM roles/policies to enable secure data flow between IIA, upstream data providers, and downstream consumers.

Build and maintain infrastructure for AI agent runtime environments, including compute resources for LangGraph agents deployed via LangSmith Deployments.

Support deployment and operation of AWS Neptune for the network topology graph (digital twin), including capacity planning, schema design support, and performance tuning.

Implement and manage infrastructure-as-code (Terraform, CloudFormation) for repeatable, auditable environment provisioning.

Manage IAM access key rotations, secrets management (AWS Secrets Manager, Delinea), and security compliance for on-premises and cloud integrations (e.g., Splunk Edge Processor).

CI/CD and Agent Deployments:

Build and maintain CI/CD pipelines for AI agent deployments using GitLab CI/CD, Docker, and Artifactory.

Manage container lifecycle for agents deployed via LangSmith Deployments, including image builds, versioning, and rollback procedures.

Automate deployment workflows to enable rapid, reliable promotion of agents from development through production.

Coordinate with SpecGPT platform team on AI Gateway integration, cross-account deployment, and connectivity requirements.

Application Development and Tooling:

Develop and maintain utilitarian application code: scripts, CLIs, small services, and automation utilities (primarily Python) that support data ingestion, deployment, environment provisioning, and operational workflows.