JOB TITLE: Platform Engineer IV Denver, CO
JOB SUMMARY
Charter's 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 Charter's 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 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 AND RESPONSIBILITIES
Responsibilities span 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.
Design and implement event-driven infrastructure including triggers, message queues, and pub/sub frameworks that orchestrate agent execution and data pipeline workflows
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
Support and maintain existing ETL pipelines written in Scala/Spark, including troubleshooting, enhancements, and onboarding new data sources.
Develop and maintain application code: scripts, CLIs, small services, and automation utilities (primarily Python) that support data ingestion, deployment, environment provisioning, and operational workflows.
Write integration code and glue services that connect IIA systems with upstream data providers, downstream consumers, and external platforms.
Production Operations
Ensure production environment stability through monitoring, alerting, and incident response. Maintain SLAs for data pipeline availability and agent uptime.
Implement production monitoring and alerting for deployed agents (health checks, error rates, latency, resource utilization).
Coordinate with upstream data teams and platform teams (SpecGPT, Splunk, Public Cloud) on connectivity, firewall requests, and integration requirements.
Support data engineering team with infrastructure needs for new data source onboarding (storage provisioning, access controls, pipeline compute) and coordinate on scheduler maintenance and development (Airflow, event-driven triggers).
Perform other duties as required.
REQUIRED QUALIFICATIONS
Skills/Abilities and Knowledge
Ability to read, write, speak and understand English
Strong communication skills with ability to explain infrastructure decisions to non-infrastructure stakeholders
Expert-level experience with AWS services: EC2, S3, IAM, VPC, Glue, Athena, EMR, Secrets Manager, CloudWatch
Strong experience with infrastructure-as-code (Terraform preferred, CloudFormation acceptable)
Experience managing cross-account AWS architectures, VPC peering, PrivateLink, and transit gateway configurations
Experience with IAM policy design, least-privilege access patterns, and service account management
Experience with containerization (Docker) and container orchestration
Experience with CI/CD pipelines (GitLab CI preferred)
Experience with event-driven architectures and messaging systems (e.g., Kafka, SNS/SQS, EventBridge)
Proficiency with Linux-based operating systems and shell scripting
Experience with monitoring and alerting tools (CloudWatch, Prometheus, Grafana, or similar)
Understanding of networking fundamentals: DNS, CIDR, NAT, VPC endpoints, firewalls, security groups
Demonstrated ability to work across teams and coordinate with external platform owners on connectivity and access requirements
Proficiency in Python (or a comparable general-purpose language) for building automation, tooling, and applications
Solid software engineering fundamentals: Git-based workflows, code review, modular and reusable design, dependency management, and writing maintainable, documented code
Experience writing automated tests (unit/integration) for application and infrastructure code, and integrating those tests into CI/CD
Ability to write integration code against REST APIs and cloud SDKs (e.g., AWS SDK / boto3)
PREFERRED QUALIFICATIONS
Skills/Abilities and Knowledge
Experience with graph databases (AWS Neptune, Neo4j) including deployment, scaling, and operational management
Experience with Apache Kafka or similar streaming platforms
Experience with Apache Spark (Scala preferred) for distributed and streaming data processing such as Spark Streaming or structured streaming.
Experience with Airflow or similar workflow orchestration platforms
Experience in the telecommunications industry or other large-scale network operations environments
Familiarity with AI/ML infrastructure requirements (model serving, GPU/CPU compute, artifact management via MLflow or similar)
Experience with Splunk integration, particularly Edge Processor and MCP connectivity
AWS certifications (Solutions Architect, DevOps Engineer, or similar)
Experience developing and operating small services or APIs (e.g., FastAPI/Flask) in a production environment
Education
Bachelor's degree in Computer Science, Information Technology, Systems Engineering, or related field, or relevant experience
Related Experience
Bachelor's degree: 5+ years of platform/infrastructure engineering experience
Master's degree: 3+ years of platform/infrastructure engineering experience
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