Platform Engineer

• Collaborate with data platform architects to design and specify platform tooling, services, and integrations
• Build data lake and lake house architectures
• Build streaming data architectures to support data platform tooling and services
• Collaborate with software teams to integrate streaming and batch architectures with software products
• Collaborate with data scientists, analysts, and business stakeholders to MVP optimal solutions
• Collaborate with data governance teams and data platform architects to build governance into technical solutions
• Maintain systems and services that provide transparency and observability into our critical systems
• Implement and promote engineering and architectural patterns, perform code reviews, and collaborate in architectural reviews
• Collaborate with product team data engineers and architects to MVP data products, maintain data models, and promote data modeling best practice
• Provide technical leadership and mentorship to product and data engineers, guiding their growth and professional development and enabling their ability to use platform tooling and services
• Lead by example through hands-on contributions to designing, coding, and troubleshooting complex data systems
• Identify and address performance bottlenecks and optimization opportunities within data pipelines, databases, and processing frameworks
• Optimize data processing workflows to improve efficiency and reduce latency
• Lead efforts to diagnose and resolve data-related incidents in a timely manner
• Will participate in the grooming of stories
• Will be responsible for their own tasking towards the completion of stories
• Will mentor junior members of the team and guide junior members on best practice
• Will participate in design
• Will be responsible for the quality of their own code and will participate in code review of others product
• Will be responsible for integrating their own code with the team's DevOps plan and implementation

Data Platform Engineer

• Provision complete infrastructure stacks for new product launches. Recent examples include full EKS buildouts (Karpenter, Istio, Crossplane), PostgreSQL/Redis data stores with IAM authentication, CloudFront distributions, and Datadog instrumentation across multiple concurrent initiatives.
• Lead Kubernetes platform evolution. Drive cluster upgrades, add-on lifecycle (Karpenter, Istio, Crossplane), pod identity migration, and namespace management across all environments.
• Design secure, scalable abstractions that hide infrastructure complexity and define the golden paths other teams build on.
• Own authentication infrastructure for internal and external products: Auth0 SSO, Azure AD/Entra, AWS IAM, EKS Pod Identity, and OIDC federation.
• Drive zero-trust infrastructure patterns. Rotating IAM credentials for RDS, per-app Istio authorization policies, and network isolation.
• Enable LLM-powered workflows (Bedrock, Claude Code, and similar) that let engineering teams move faster without sacrificing governance.

Senior Platform Engineer

• Evaluate, design and implement technology solutions to build and progress technology strategies with a line of business.
• Be the main liaison with software vendor(s) for systems utilized by a particular line of business.
• Stay abreast of upcoming changes and enhancements in vendor’s software and how those changes will impact the business.
• Work with the line of business to design solutions to incorporate software changes and effectively work with business partners to ensure effective implementation.
• Understand the business technology roadmap and make recommendations on continued utilization or elimination of current third party software solutions.
• Implement and maintain new features and capabilities while continuously improving the quality of our technical products and services.
• Provide operational support and troubleshooting for your team’s products and services.
• Provide coaching, mentoring, and training for new or less experienced team members.

Lead Platform Engineer

• Serve as a senior technical owner for Linux server operating systems, with deep expertise in Red Hat Enterprise Linux 9 and 10.
• Define, maintain, and evolve Linux platform standards, including build standards, configuration baselines, hardening guidelines, and lifecycle strategies.
• Create and maintain product roadmaps that align Linux platform capabilities with business, security, and regulatory requirements.
• Research, evaluate, and experiment with emerging Linux related technologies, determining their applicability and value to the enterprise.
• Translate evaluated technologies into tested, documented, and repeatable platform solutions, including proofs of concept and pilot implementations.
• Lead solutions from concept through pilot and into full enterprise adoption, working with provisioning, security, and operations teams as needed.
• Design and maintain server build templates and reference architectures used by downstream provisioning teams.
• Produce clear, high quality documentation, including standards guides, configuration guides, hardening guides, and standard operating procedures, with the intent of enabling scale rather than performing operational execution.
• Ensure the Linux platform remains secure, current, and sustainable over time.

Senior Technology Engineer – Linux Platform

• Help in designing, building, and operating the university’s shared data infrastructure – including data pipelines, medallion-layer and other framework data products, cloud and/or on-prem tooling, and the integration fabric that connects data systems across the university.
• Help realize the design and build of ETL/ELT and other data integration movement processes for the Reporting and Analytics Environment.
• Engage with other data engineers and enterprise/integration architects within the team.
• Collaborate with OTDI Infrastructure colleagues and specialists in designing and implementing integrations from multiple systems into the team's data environments.
• Work to obtain and refine data requirements, build data integration flows, partner with data and visualization analysts on query optimization and tuning, and confer with data governance resources on metadata requirements.
• Provide production support duties for the systems we manage; respond to help desk issues related to our systems, monitor the production support queue, and respond to data flow failures in a timely manner.
• Participate in rotating off-hours and weekend on-call/pager duty.

Senior Data Platform Engineer

• Monitor OCI service health, logs, dashboards, and alerts.
• Troubleshoot platform issues and customer environment concerns.
• Support development teams with infrastructure questions and deployment needs.
• Manage CI/CD pipeline performance and resolve deployment failures.
• Execute provisioning, onboarding, and configuration requests.
• Update documentation and architecture artifacts as infrastructure evolves.
• Participate in standups, planning meetings, and technical reviews.
• Review OCI consumption reports, billing dashboards, and cost optimization opportunities.
• Conduct IAM, security, and credential audits.
• Evaluate reference architecture environments for configuration drift and required updates.
• Refine deployment methodologies, runbooks, and onboarding documentation.
• Assess Oracle OCI roadmap updates and emerging platform capabilities.
• Contribute technical documentation, architecture guidance, and internal knowledge-sharing content.

AI Platform Engineer

• Define the strategy for AI-augmented firmware architectures.
• Architect automated orchestration frameworks to streamline system requirements.
• Design and develop firmware for professional tools with embedded electronics.
• Lead system design, including architecture design and system requirements development.
• Conduct concept feasibility assessments and technical risk evaluations.
• Provide technical leadership to uphold software quality standards.
• Mentor junior engineers and support field investigations throughout the product lifecycle.

Embedded Systems Platform Engineer

• Provision and manage cloud infrastructure across compute, networking, storage, and managed databases
• Maintain consistency across development, staging, and production environments
• Plan and execute workload migrations across cloud providers with minimal disruption
• Identify and implement infrastructure cost optimization opportunities
• Build and maintain CI/CD pipelines across a multi-repository environment
• Implement deployment strategies such as blue/green, canary, and rolling deployments
• Develop automation tooling and scripts to reduce manual effort and improve delivery speed
• Write and maintain Terraform infrastructure across multi-account, multi-environment systems
• Establish IaC standards, module reuse patterns, and state management practices
• Drive infrastructure changes through version-controlled, peer-reviewed workflows
• Participate in on-call rotation and lead incident response efforts
• Maintain observability through dashboards, alerting, logging, and SLO tracking
• Conduct post-incident reviews and implement long-term remediations
• Manage secrets, certificates, and access controls using least-privilege principles
• Apply security best practices across infrastructure, containers, and CI/CD pipelines
• Support audit and compliance initiatives through documentation and access reviews
• Partner with engineering teams on infrastructure guidance and service design
• Create architecture documentation, runbooks, and operational guides
• Help build self-service platform capabilities for engineering teams

• Run hands-on technical discovery across assigned domains — typically cost governance, observability, platform deployment, and management tooling — using Azure Resource Graph, Azure Policy compliance, Microsoft Cost Management, Defender for Cloud, Microsoft Entra reporting, Azure Monitor, and Application Insights.
• Review the client’s existing Terraform footprint and common Azure DevOps deployment paths. Identify standardization opportunities, configuration drift risks, and the foundational moves required to mature toward a code-driven, team-owned platform.
• Assess tagging standards and enforcement, automated alerts and reporting, and Reserved Instance and Savings Plan utilization. Propose practical cost-governance improvements that hold up as Azure adoption grows.
• Evaluate the centralized logging, monitoring, and alerting strategy, including SIEM integration patterns, audit log retention posture, and the application telemetry surface exposed through Azure Monitor and Application Insights.
• Draft the sections of the report tied to your streams of work — findings, recommendations, effort indications, and success-criteria tagging — to a quality bar that lets the Principal Consultant integrate them into the broader narrative with minimal rework.
• Produce the tangible artifacts that Callibrity is known for during assessment engagements: working dashboards, reusable IaC modules, governance-as-code samples, or developer-experience prototypes where they accelerate the client’s ability to act on the recommendations.
• Participate in stakeholder interviews and on-site working sessions. Bring engineering credibility to the conversation, not just note-taking.

Senior Cloud and Platform Engineer

• As a Senior Data Platform Engineer, you’ll be a hands-on engineer on a small, high-ownership data team.
• You’ll work across the full data platform - relational, warehouse, and lakehouse systems - building and operating the pipelines that power compliance, analytics, and reporting workloads.
• Design and build pipelines that move data across systems - supporting data lake ingestion, compliance workloads, and cross-domain data flows.
• Own pipeline operations end to end: monitoring, incident resolution, data quality, and documentation that lets any team member respond independently.
• Identify technical debt and reliability risks and raise them with clear context and proposed next steps.
• Design and maintain schemas across relational, warehouse, and lakehouse layers, working with application engineers and product to get data models right.
• Build out the platform’s service layer, infrastructure-as-code, and data quality frameworks - this role spans design and implementation.
• Keep platform documentation at a level where any team member can understand what exists, how it works, and where the risks are.
• Over time, contribute to the analytics engineering layer, including modeling practices and semantic layer development.
• Contribute to evaluations of the current platform against emerging architectures and tooling, helping produce trade-off analyses and recommendations.
• Bring what you see day to day in the systems you operate into the team’s improvement roadmap and technical direction.
• Track and report on platform health metrics: pipeline uptime, failure rates, data freshness, and cost trends.
• Mentor peers and junior engineers through code review, pairing, and technical guidance.

• Develop innovative solutions for secure operations of enterprise systems
• Engineer, design, and implement cyber defense capabilities
• Prevent network threats and identify attack vectors
• Provide guidance and direction to lower-level technicians and specialists

Data Analytics Platform Engineer

• Contribute toward the success of developing a modern analytics platform for the business.
• Deep understanding of cloud provider features (Azure or AWS) regarding networking, storage, and IAM.
• Building and using automation pipelines for CICD and Databricks Asset Bundles.
• Managing workspaces, compute resources, and other related activities.
• Designing, developing, testing, operating, and maintaining products.
• Writing production-ready and testable code.
• Reviewing tasks and ensuring they are appropriately prioritized and sized for incremental delivery.

Senior Data Analytics Platform Engineer – Databricks

• Build and maintain core platform services including the LLM gateway, model registry
• Implement AI Foundry-based capabilities and integrate them with existing enterprise platforms
• Develop reusable Python and/or Java libraries, SDKs, and golden-path templates
• Own automation that provisions access, onboards models, runs compliance checks
• Design and operate retrieval pipelines including chunking, embedding, vector store management
• Tune retrieval quality against real consumer workloads
• Build, host, and operate MCP servers that expose enterprise capabilities safely
• Own the on-call rotation for the services you build

• Responsible for the overall health, security, resiliency, and performance of System z CICS for z/OS, MQ for z/OS, and z/OS zCEE across multiple Sysplexes and CECS
• Responsible for the z/OS networking for CICS, MQ and zCEE connectivity requirements (TCPIP, LU6.2, Sockets, EXCI, ETC.)
• Manage overall platform documentation, reports including all KPIs, charts, end-to-end workflow diagrams of all system z software zCEE, CICS and MQ
• Develop and present z/OS zCEE, CICS and MQ, HA (SYSPLEX/CICSPLEX roadmaps)
• Lead problem troubleshooting efforts and root cause analyses of all P1 & P2 System z zCEE, CICS and MQ related incidents
• Develop, document, and deliver pre- and post-implementation analysis of System z tech refreshes and application releases
• Eliminate reoccurring issues and drive down mean time to recovery
• Provide technical direction and education to programmers, analysts, and technical support associates
• Prototypes the new features, functions, and strategies of new application subsystems technology.
• Provides 24x7 on call support within a team rotation.

Lead Mainframe Platform Engineer – CICS, MQ, zCEE

• Define and maintain golden paths for service creation, including service templates, starter kits, and scaffolding tools that let teams go from zero to production-ready with minimal friction
• Own developer onboarding workflows and maintain high-quality platform documentation
• Establish and evolve CI/CD pipeline standards across the organization
• Design release automation patterns, including rollout safety mechanisms such as canary deployments, progressive delivery, and automated rollbacks
• Build and maintain internal platform portals, reusable infrastructure modules, and paved-road workflows
• Enable product engineering teams to provision resources, configure environments, and ship features independently without reliance on other teams
• Champion platform adoption through clear documentation, enablement sessions, and a consultative approach
• Measure developer satisfaction and platform adoption metrics to continuously improve the experience
• Partner with product engineering, infrastructure, and operations teams to ensure platform tooling meets cross-platform needs
• Translate engineering pain points into scalable platform capabilities• Embed security and compliance requirements such as SOC2 and PCI-DSS into platform tooling and CI/CD pipelines

• Design, build, and operate large-scale, on‑premises GPU infrastructure
• Lead advanced Linux system administration and platform initiatives
• Architect, deploy, and operate containerized GPU workloads using Kubernetes and related tooling
• Manage, optimize, and troubleshoot NVIDIA GPU environments at scale
• Support and improve cluster scheduling, capacity planning, and resource management
• Diagnose and resolve complex, cross-cutting, or poorly defined infrastructure issues
• Collaborate closely with application, research, and infrastructure teams to enable GPU workloads and drive platform adoption
• Take ownership of complex or ambiguous problems and drive them to resolution
• Provide technical guidance, mentoring, and occasional leadership on platform design and operational decisions
• Influence platform direction through hands-on expertise, architectural input, and operational insight
• Drive continuous improvements in platform reliability, scalability, performance, and operational excellence

Lead Software Engineer – GPU Platform Engineer

• Own the operational lifecycle of AI agents deployed across PEMCO: deployment, monitoring, scaling, incident response, and retirement.
• Build and maintain observability for the AI layer, including cost tracking, latency, error rates, model performance, token usage, and production monitoring for agent workers.
• Manage agent orchestration infrastructure, including configuration, versioning, connection management, and tool registration. Current stack includes MCP-based orchestration and Azure OpenAI services.
• Establish runbooks and incident response procedures for AI agent failures. When an agent supporting a business workflow goes down, this role owns the recovery.
• Implement prompt governance controls and role-based model access per Information Security standards: PII exposure monitoring, prompt injection detection, and access enforcement. Contribute requirements and technical capabilities to InfoSec for AI-specific policy development.
• Build the enterprise agent marketplace: deploy and manage AI agents within an enterprise UI framework, ensuring discoverability, versioning, and access controls.
• Evaluate new model releases, track capability evolution, and make recommendations on model selection. Maintain a knowledge management layer for AI operations including decision logs, model inventories, and governance documentation.
• Contribute directly to AI governance and the AI Governance Working Group. Operationalize security, governance, and compliance standards defined by Information Security and Data & AI leadership across all AI deployments.
• Optimize AI infrastructure costs through model selection, caching strategies, batching, and token budget management.
• Partner with the Data & AI team on production readiness for models and agents. Data & AI owns model development, training, and AI governance policy. This role owns the operational deployment, monitoring, fallback behavior, graceful degradation, and knowledge layer integration.
• As the function matures, define team structure, secure headcount, and build a team.
• Demonstrate behaviors consistent with PEMCO's policies, values, code of ethics, and business conduct.
• Authentically support the PEMCO Brand and constantly are on the lookout for top talent to join us to achieve our Mission to Worry Less and Live More.
• Other duties as assigned.

Principal AI Platform Engineer

• Own the design, configuration, and continuous improvement of the Freshservice platform
• Design and implement end-to-end service catalog solutions, including forms, workflows, approvals, routing, and automated fulfillment
• Develop and maintain integrations using APIs, webhooks, and middleware to extend platform capabilities
• Evaluate, test, and implement new platform features, modules, and enhancements
• Establish platform standards, including workflow design, naming conventions, and data governance practices
• Build automation solutions to reduce manual effort and improve service delivery efficiency
• Document configurations, workflows, and integrations to support knowledge transfer and long-term sustainability
• Design and deploy Device42 integration for automated asset discovery and infrastructure visibility
• Design and implement ITAM capabilities within Freshservice, including hardware and software asset tracking, lifecycle workflows, and procurement integration
• Build and administer asset lifecycle workflows: procurement, assignment, maintenance, and disposition
• Develop asset reporting, reconciliation processes, and automated discovery synchronization
• Design and implement ITOM capabilities, including discovery, event management, and orchestration
• Integrate monitoring and alerting tools to enable centralized event management, alert correlation, and noise reduction
• Develop automation runbooks and workflows to streamline operational tasks and incident response
• Build service health dashboards and operational views for critical business services
• Define event classification and routing logic to improve response times and operational efficiency
• Define and implement the CMDB data model, including CI classes, attributes, and relationship mapping
• Build and maintain configuration records for critical infrastructure, applications, and services
• Establish data quality controls, validation rules, and governance practices to ensure CMDB accuracy
• Develop service mapping capabilities to support impact analysis for Change and Major Incident Management
• Partner with technical teams to align CMDB structure with real-world service architecture

IT Service Management Platform Developer – Administrator

• Develop value-added features tailored to company specific work, above and beyond the core capabilities of the cloud platform and relevant vendor tools
• Research, experiment with, and implement suitable GenAI algorithms, tools, and technologies
• Explore new services and capabilities in AWS, Google Cloud Platform, and Azure to support GenAI and ML services
• Enhance platform functionality with strong engineering expertise in AI, ML, Agentic Frameworks, and modern data technologies
• Develop and promote best practices in AI, ML, and data engineering across teams
• Architect and design end-to-end solutions at a component level
• Collaborate with partners in Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams
• Manage engineering tasks, driving execution, and optimizing workflows with minimal guidance
• Provide technical mentorship and career growth opportunities for team members
• Review work of systems-level engineers to calibrate deliverables against project and business expectations

AI Platform Engineer – Google Cloud Platform

• Design, implement, and maintain Kubernetes-based deployment strategies for a multi-service application.
• Develop, manage, and version Helm charts supporting multiple environments (dev, test, staging, production).
• Ensure consistent deployments across on-prem (self-hosted) and cloud Kubernetes platforms.
• Implement secure configuration management (secrets, certificates, RBAC, network policies).
• Troubleshoot complex deployment, integration, and runtime issues across distributed systems.
• Serve as a primary escalation point for production issues, driving root cause analysis and resolution.
• Provide direct support to internal teams and/or customers, including issue triage, communication, and resolution tracking.
• Optimize cluster performance, resource utilization, and cost efficiency.
• Collaborate with development teams to improve containerization and deployment practices.
• Maintain system observability (logging, monitoring, alerting).
• Support compliance requirements (e.g., FIPS, STIG, hardened images, restricted networks).

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