> Markdown version of [/jobs/ext/3876568-platform-engineer](https://www.wearedevelopers.com/jobs/ext/3876568-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Platform Engineer

- **Company:** Apex Systems LLC
- **Location:** Greenwood Village, CO, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Systems Engineering, Network Analysis, Extract Transform Load (ETL), Data Security, DevOps, Graph Database, Identity and Access Management, Python (Programming Language), Neo4j, Peering, Apex Code, Computer Network Operations, Data Ingestion, Flask (Web Framework), Apache Spark, Amazon Virtual Private Cloud (VPC), Cloudformation, Fastapi, Containerization, Data Lakes, Gitlab-ci, Git Flow, Kubernetes, Information Technology, Apache Kafka, Machine Learning Operations, Virtual Agents, Cloudwatch, Terraform, Data Pipelines, Docker, Artifactory
- **Published:** October 22, 2026
- **Apply:** https://www.juju.com/job/1_25068435D0BB4564861BAF34302BCABC-CO844768666957084

## About the Role

Required Qualifications - Experience as a senior-level resource working in large-scale environments. - Expert-level experience with AWS services, including EC2, S3, IAM, VPC, Glue, Athena, EMR, Secrets Manager, and CloudWatch. - Strong experience with infrastructure-as-code, preferably Terraform. - Experience managing cross-account AWS architectures, including VPC peering, PrivateLink, and transit gateway configurations. - Proficiency with IAM policy design, least-privilege access patterns, and service account management. - Experience with containerization (Docker) and container orchestration. - Experience with CI/CD pipelines, preferably GitLab CI. - Proficiency in Python or a comparable language for building automation and tooling. - Solid software engineering fundamentals, including Git-based workflows and writing maintainable code. - Bachelor's degree in Computer Science, Information Technology, Systems Engineering, or a related field, or equivalent experience.
A Bachelor's degree should be accompanied by 5+ years of platform/infrastructure engineering experience, while a Master's degree requires 3+ years.
Preferred Qualifications - Experience with graph databases such as AWS Neptune or Neo4j. - Experience with Apache Kafka, Apache Spark (Scala preferred), and Airflow. - Familiarity with AI/ML infrastructure requirements. - Experience in the telecommunications industry or other large-scale network operations environments. - AWS certifications, such as Solutions Architect or DevOps Engineer. - Experience developing and operating small services or APIs using frameworks like FastAPI or Flask. *Everforth Apex is a world-class IT services company that serves thousands of clients across the globe.

## Description

This role ensures production environments are stable, scalable, and secure, enabling data science and agentic AI workloads to operate reliably.
You will support a Network Analytics team project that is moving from proof-of-concept to production, with a focus on enhancing the security and operational efficiency of enterprise networks.
Key Responsibilities - Design and manage AWS infrastructure for a data lake, including S3, Glue, Athena, and EMR clusters. - Manage cross-account AWS architectures, VPC networking, security groups, and IAM roles to ensure secure data flow. - Implement and manage infrastructure-as-code using Terraform or CloudFormation for repeatable environment provisioning. - Build and maintain CI/CD pipelines for AI agent deployments using tools like GitLab CI/CD, Docker, and Artifactory. - Develop and maintain application code, scripts, and automation utilities, primarily in Python, to support data ingestion, deployment, and operational workflows. - Ensure production environment stability through monitoring, alerting, and incident response, maintaining SLAs for data pipeline availability. - Support and maintain existing ETL pipelines written in Scala/Spark, including troubleshooting and onboarding new data sources. - Coordinate with upstream data teams and other platform teams on connectivity,
firewall requests, and integration requirements.