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We are seeking a Data Analyst/Cloud Capacity Planning Analyst to join a growing infrastructure team responsible for forecasting, planning, and optimizing enterprise cloud and data center resources. This role is ideal for someone who enjoys turning data into actionable insights, building forecasting models, automating processes, and partnering with engineering and business teams to ensure infrastructure is properly sized for current and future demand.

Responsibilities:

Analyze compute, storage, and infrastructure utilization trendsBuild and automate forecasting and capacity planning modelsCreate dashboards, reports, and alerts to identify capacity risksPartner with engineering, operations, application, and finance teamsSupport capacity lifecycle management, including planning, procurement, deployment, and decommissioningDrive automation and process improvement initiatives

Requirements:

3-5+ years of experience in Capacity Planning, Data Analytics, Infrastructure Analytics, or ForecastingStrong skills in Excel, SQL, and PythonExperience with reporting, modeling, and data visualizationStrong analytical and problem-solving abilitiesUnderstanding of cloud, compute, storage, virtualization, and infrastructure environments

Nice to Have:

VMware, OpenStack, Kubernetes, or container platform experienceAI/ML-based forecasting or predictive analytics experience

Ideal Backgrounds: Capacity Planning Analyst, Data Analyst, Infrastructure Analyst, Cloud Operations Analyst, Capacity Engineer, or Data Engineer with forecasting/modeling experience.

GCS is acting as an Employment Business in relation to this vacancy.

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Cloud Capacity Engineer | Private Cloud Infrastructure

We're looking for a Cloud Capacity Engineer to join a growing infrastructure engineering team supporting private cloud platforms and enterprise-scale systems.

This role sits at the intersection of cloud infrastructure, capacity planning, forecasting, data analysis, and automation. You'll help determine how much compute, storage, networking, power, rack space, and cooling capacity is needed to support future growth.

You'll work closely with application development teams, infrastructure engineers, operations, procurement, and finance to make sure infrastructure capacity aligns with business and technology demands.

What You'll DoBuild and automate tools for infrastructure capacity planning, forecasting, and sizingDevelop forecasting models to predict long-term growth of computing resourcesAnalyze utilization and performance of compute and storage environmentsSupport capacity planning for private cloud environments, including VMs and containersHelp determine data center power, rack, and cooling requirementsValidate infrastructure procurement requirements using models and architecture designsPartner with compute, storage, and network engineering teams on infrastructure designs and bills of materialsSupport infrastructure scaling, future growth, and capacity augmentation decisionsIdentify underutilized resources and opportunities for improved efficiencyPartner with finance on capacity planning and future technology budgetsEvaluate capacity data and thresholds to identify potential performance or availability risksDevelop and maintain infrastructure capacity planning frameworks and inventoryAutomate processes and identify opportunities to improve infrastructure planningWhat We're Looking ForApproximately 3-5+ years of hands-on experience in infrastructure analytics, capacity planning, forecasting, or related engineeringExperience working with cloud or private cloud infrastructureUnderstanding of compute, virtualization, storage, and networkingExperience with data analysis, modeling, forecasting, or capacity managementStrong analytical and problem-solving skillsExperience automating tools or processesAbility to work cross-functionally with application and infrastructure engineering teams

If you enjoy using data and engineering to answer "How much infrastructure do we need, when will we need it, and how can we use it more efficiently?" this could be a great opportunity.

GCS is acting as an Employment Business in relation to this vacancy.

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Position Summary

We are seeking a Machine Learning Engineer to join a high-performing AI and Data Science team responsible for developing, deploying, and maintaining predictive machine learning solutions. This role will focus on designing end-to-end ML pipelines, building scalable predictive models, and operationalizing machine learning workloads in a cloud-based environment.

The ideal candidate will possess strong expertise in Python, PySpark, machine learning frameworks, data analysis, and MLOps practices. Experience working with Large Language Models (LLMs) and deploying machine learning solutions in AWS environments is highly desired.

Key Responsibilities

Design, develop, and deploy machine learning models focused on predictive analytics and business intelligence use cases.Build scalable data processing and feature engineering pipelines using PySpark and distributed computing technologies.Develop, test, and optimize machine learning algorithms using Python and Scikit-learn.Implement and maintain end-to-end MLOps pipelines for model training, deployment, monitoring, and lifecycle management.Work with large structured and unstructured datasets to derive actionable insights and improve model performance.Collaborate with data scientists, software engineers, and business stakeholders to translate requirements into production-ready ML solutions.Support the integration of machine learning models into enterprise applications and workflows.Leverage AWS cloud services to build scalable and reliable machine learning infrastructure.Explore and implement Large Language Model (LLM) solutions where applicable.Participate in model evaluation, performance tuning, and continuous improvement initiatives.

Required Qualifications

5+ years of experience in Machine Learning Engineering, AI Engineering, or related disciplines.Strong programming expertise in Python.Hands-on experience with PySpark and large-scale data processing.Experience developing machine learning models using Scikit-learn.Strong background in data analysis, feature engineering, and statistical modeling.Experience building and maintaining MLOps pipelines and model deployment workflows.Knowledge of machine learning lifecycle management, CI/CD, and production model monitoring.Experience working within AWS cloud environments.Familiarity with Large Language Models (LLMs), NLP, or Generative AI technologies.Strong problem-solving and communication skills.

Preferred Qualifications

Experience developing Neural Network models using frameworks such as PyTorch or TensorFlow.Experience with workflow orchestration and pipeline management tools.Exposure to predictive AI solutions and advanced forecasting models.Knowledge of distributed machine learning and scalable AI infrastructure.Experience supporting enterprise-scale machine learning deployments.

Technical Environment

PythonPySparkScikit-learnAWSMLOpsLarge Language Models (LLMs)Machine Learning PipelinesPredictive AnalyticsNeural Networks (Preferred)PyTorch / TensorFlow (Preferred)

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Position Summary

We are seeking a Machine Learning Engineer to join a high-performing AI and Data Science team responsible for developing, deploying, and maintaining predictive machine learning solutions. This role will focus on designing end-to-end ML pipelines, building scalable predictive models, and operationalizing machine learning workloads in a cloud-based environment.

The ideal candidate will possess strong expertise in Python, PySpark, machine learning frameworks, data analysis, and MLOps practices. Experience working with Large Language Models (LLMs) and deploying machine learning solutions in AWS environments is highly desired.

Key Responsibilities

Design, develop, and deploy machine learning models focused on predictive analytics and business intelligence use cases.Build scalable data processing and feature engineering pipelines using PySpark and distributed computing technologies.Develop, test, and optimize machine learning algorithms using Python and Scikit-learn.Implement and maintain end-to-end MLOps pipelines for model training, deployment, monitoring, and lifecycle management.Work with large structured and unstructured datasets to derive actionable insights and improve model performance.Collaborate with data scientists, software engineers, and business stakeholders to translate requirements into production-ready ML solutions.Support the integration of machine learning models into enterprise applications and workflows.Leverage AWS cloud services to build scalable and reliable machine learning infrastructure.Explore and implement Large Language Model (LLM) solutions where applicable.Participate in model evaluation, performance tuning, and continuous improvement initiatives.

Required Qualifications

5+ years of experience in Machine Learning Engineering, AI Engineering, or related disciplines.Strong programming expertise in Python.Hands-on experience with PySpark and large-scale data processing.Experience developing machine learning models using Scikit-learn.Strong background in data analysis, feature engineering, and statistical modeling.Experience building and maintaining MLOps pipelines and model deployment workflows.Knowledge of machine learning lifecycle management, CI/CD, and production model monitoring.Experience working within AWS cloud environments.Familiarity with Large Language Models (LLMs), NLP, or Generative AI technologies.Strong problem-solving and communication skills.

Preferred Qualifications

Experience developing Neural Network models using frameworks such as PyTorch or TensorFlow.Experience with workflow orchestration and pipeline management tools.Exposure to predictive AI solutions and advanced forecasting models.Knowledge of distributed machine learning and scalable AI infrastructure.Experience supporting enterprise-scale machine learning deployments.

Technical Environment

PythonPySparkScikit-learnAWSMLOpsLarge Language Models (LLMs)Machine Learning PipelinesPredictive AnalyticsNeural Networks (Preferred)PyTorch / TensorFlow (Preferred)

GCS is acting as an Employment Business in relation to this vacancy.

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Role: Looker SME

Job Summary

We are seeking an experienced Looker Administrator to support platform engineering, cloud migration initiatives, data platform modernization, and operational excellence within a large-scale analytics environment. The ideal candidate will have strong expertise in Looker administration, LookML development, BI platform support, cloud technologies, identity management, and performance optimization.

Key Responsibilities

Platform Engineering & Operations

Provide L3/L4 production support for Looker environments across development and production platforms.Lead platform upgrades, releases, patch management, and validation activities.Support GitHub and LookML development workflows, including Dev/Prod deployments and coordination.Troubleshoot and resolve complex performance, scalability, and data modeling issues.Monitor platform health, reliability, and operational performance.

Access Management, Governance & Identity

Implement and maintain automated user provisioning and entitlement management processes.Investigate and resolve access-related issues, including Azure AD synchronization and entitlement discrepancies.Establish governance standards, security controls, and platform usage guidelines.Create and maintain governance documentation and operational procedures.

API Integration & Advanced Analytics Use Cases

Support and administer Looker APIs, including Inline Query APIs, Query ID APIs, and Administrative APIs.Validate platform performance, concurrency, and usage patterns.Enable API-driven analytics initiatives and AI-powered reporting solutions.Collaborate with engineering teams to support dynamic SQL generation and advanced automation requirements.

Cloud Migration & Modernization

Support migration activities from customer-hosted environments to Google-hosted Looker Core.Define, execute, and validate testing strategies for migration initiatives.Participate in proof-of-concept (POC) activities while minimizing platform risk.Ensure platform stability, security, and performance during migration efforts.

Data Platform Modernization

Support query validation and reporting consistency across modern cloud data platforms.Collaborate with data engineering teams to standardize semantic models, query behavior, and performance expectations.Validate data accuracy and reporting outcomes during platform transformation projects.Optimize reporting performance and data accessibility across enterprise analytics environments.

Documentation & Knowledge Transfer

Develop comprehensive documentation, runbooks, operational procedures, and best practices.Conduct knowledge transfer sessions and mentor internal engineering teams.Support long-term platform ownership transition through training and process standardization.Maintain technical documentation for administration, troubleshooting, and operational support.

Required Qualifications

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.5+ years of experience administering Business Intelligence or Analytics platforms.Hands-on experience with Looker administration and LookML development.Strong knowledge of GitHub version control and CI/CD deployment practices.Experience with Azure Active Directory (Azure AD) integration and identity management.Proficiency in REST APIs and platform automation.Experience supporting cloud-based analytics environments.Strong SQL skills and experience troubleshooting complex query performance issues.Excellent problem-solving, communication, and documentation skills.

Preferred Qualifications

Experience with Google Cloud Platform (GCP).Experience with Snowflake and Teradata environments.Knowledge of enterprise data governance and security frameworks.Experience supporting cloud migration and modernization initiatives.Exposure to AI-enabled analytics, automation, and API-driven reporting solutions.

Required Skills

Looker AdministrationLookML DevelopmentGitHub & Version ControlSQL Performance TuningREST APIsAzure ADIdentity & Access Management (IAM)Cloud Analytics PlatformsData GovernanceSnowflakeTeradataDocumentation & Knowledge TransferProduction Support (L3/L4)Platform Upgrades & Release Management

GCS is acting as an Employment Business in relation to this vacancy.

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DevOps / Automation Engineer

We're looking for a DevOps / Automation Engineer to support the design, development, implementation, and ongoing support of production software systems. This role is a strong fit for someone who enjoys automation, deployment, troubleshooting, and working closely with software engineering and QA teams.

What You'll Do

Design, develop, implement, and analyze technical products and systems

Troubleshoot, diagnose, and resolve production software issues

Develop monitoring solutions and perform ongoing software maintenance

Automate software deployment and operational processes

Develop standards and procedures for product quality and release readiness

Recommend improvements to testing techniques, development processes, and system reliability

Provision and manage applications across virtual and cloud infrastructure

Work closely with QA and Software Engineers to support continuous delivery of critical systems

Support deployment and network operations through scripting and automation

What We're Looking For

Bachelor's degree in Engineering or a related field

3-6 years of relevant engineering, DevOps, systems, or infrastructure experience

Experience with automation tools such as Puppet, Chef, or Ansible

Experience with Jenkins and continuous integration

Experience with GitHub, including branching and tagging strategies

Experience with Docker and Kubernetes

Experience working with systems and IT operations

Strong scripting and coding capabilities

Experience with virtual and cloud infrastructure; AWS and OpenStack preferred

Ability to work with a variety of open-source technologies and tools

Strong communication and relationship-building skills with QA and Software Engineering teams

Ideal Background
Candidates coming from DevOps, infrastructure engineering, systems engineering, deployment engineering, or automation-focused roles are encouraged to apply.

GCS is acting as an Employment Business in relation to this vacancy.

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Senior Systems/Application Engineer

Are you a senior technology professional who enjoys working across the full application lifecycle?

We're looking for an experienced Systems/Application Engineer to join a technology team supporting complex business and IT solutions. This is a great opportunity for someone who can bridge business requirements with hands-on technical design, development, testing, implementation, and ongoing application support.

What you'll be doing:
* Partner with customers, business analysts, and technical teams to understand business requirements
* Design and develop scalable technical solutions aligned with IT and architectural standards
* Participate throughout the full systems development lifecycle
* Design, code, test, implement, maintain, and support application software
* Evaluate opportunities to build new solutions or reuse existing code
* Contribute to application, component, and data architecture decisions
* Support performance monitoring, product evaluation, and integration activities
* Help deliver solutions on time and within budget

What we're looking for:
* 10+ years of programming and/or systems analysis experience
* Strong understanding of software development, QA, testing, and integration methodologies
* Experience translating business requirements into technical solutions
* Strong systems analysis and application design experience
* Bachelor's degree in Computer Science, Information Systems, or related field - or equivalent experience

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Job Summary

We are seeking an experienced Senior Application Developer / Systems Analyst to design, develop, implement, and support enterprise applications. The ideal candidate will work closely with business stakeholders and technical teams to deliver scalable, high-quality solutions aligned with business goals and architectural standards.

Key ResponsibilitiesGather and analyze business and technical requirements.Design, develop, test, deploy, and support application solutions.Participate in all phases of the Software Development Life Cycle (SDLC).Develop high-quality, reusable, and maintainable code.Recommend new development approaches and code reuse opportunities.Contribute to application, component, and data architecture design.Monitor application performance and resolve production issues.Support system integrations, product evaluations, and build-vs-buy assessments.Ensure timely delivery of solutions that meet quality standards.QualificationsBachelor's degree in Computer Science, Information Systems, or a related field (or equivalent experience).10+ years of experience in software development and systems analysis.Strong knowledge of application development, system integration, and SDLC methodologies.Experience with application design, testing, implementation, and production support.Excellent analytical, problem-solving, and communication skills.

GCS is acting as an Employment Business in relation to this vacancy.

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Position Overview

We are seeking a Fiber Engineer to support the installation, testing, troubleshooting, maintenance, and deployment of fiber-optic network infrastructure.

The role focuses on the design, implementation, testing, and maintenance of fiber networks supporting telecommunications, enterprise, and network infrastructure services. The Fiber Engineer will work with fiber-optic systems, cabling, network equipment, and testing tools to ensure reliable network performance and connectivity.

The ideal candidate has hands-on experience with fiber-optic infrastructure, network installations, testing, troubleshooting, and maintenance, with the ability to work in field, customer, data center, and communications environments.

Responsibilities

Install, test, troubleshoot, and maintain fiber-optic network infrastructure.

Perform fiber installations, terminations, splicing, and network connectivity activities.

Conduct fiber testing and certification using industry-standard testing equipment.

Perform optical measurements, loss testing, and fault isolation.

Troubleshoot fiber and connectivity issues and identify the root cause of network problems.

Perform inspections and preventative maintenance on fiber infrastructure.

Support fiber network deployments, upgrades, expansions, and service activations.

Work with network and communications equipment connected to fiber infrastructure.

Perform testing and validation following installation, repair, or network modifications.

Support network restoration and emergency repair activities when required.

Read and interpret fiber documentation, network diagrams, drawings, and installation specifications.

Maintain accurate records of fiber routes, testing results, splicing activities, equipment, and maintenance work.

Coordinate with field engineers, network engineers, contractors, customers, and operations teams.

Follow established safety, installation, testing, and industry procedures.

What You Will Learn

Hands-on experience with fiber-optic network infrastructure.

Fiber installation, termination, splicing, testing, and maintenance techniques.

Fiber troubleshooting and optical fault-isolation methods.

How to use professional fiber testing and certification equipment.

Optical loss, power-level, and fiber-performance testing.

Fiber network documentation, diagrams, and infrastructure records.

How fiber networks support telecommunications and enterprise services.

Network restoration and emergency fiber-repair procedures.

Best practices for working in field, data center, customer, and communications environments.

Preventative maintenance and fiber network quality-control processes.

Coordination between fiber, network, engineering, and field-service teams.

Career development toward Senior Fiber Engineer, Fiber Optic Technician, Network Engineer, Optical Engineer, Transport Engineer, or Fiber Design Engineer roles.

GCS is acting as an Employment Business in relation to this vacancy.

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Role- Full Stack Pythomn Developer
Type- Contract
Duration- 12+ months
Location- Philadelphia, PA

Overview

Seeking a Full Stack Python Developer to build AI-driven security automation solutions within a Cyber Security Operations Center (CSOC). This is a hands-on engineering role focused on developing intelligent agents and automated workflows that improve threat detection, investigations, and incident response.

Key Responsibilities

Design, develop, deploy, and maintain production-grade security automation and AI-powered workflows.Build AI agents capable of accessing security data, using tools, maintaining context, and executing multi-step tasks.Automate processes across:Threat IntelligenceThreat HuntingDetection EngineeringSecurity InvestigationsIncident ResponseSecurity Data AnalysisApply advanced AI techniques including:Tool CallingRetrieval-Augmented Generation (RAG)Structured GenerationPlanning & ReflectionVerificationModel RoutingMulti-Agent CoordinationDesign memory, context management, task recovery, escalation, and human approval mechanisms.Reduce false positives and operational noise while improving response speed and consistency.Develop security controls and guardrails for AI systems.Create testing and evaluation frameworks to measure AI accuracy, reliability, security, and performance.Collaborate with security and engineering teams to translate operational challenges into scalable automation solutions.Take solutions from prototype to production and continuously optimize them.

Required Qualifications

Bachelor's degree in Computer Science, Cybersecurity, Engineering, Information Systems, or related field (or equivalent experience).8+ years of experience in software engineering, security engineering, automation, AI/ML, or related technical roles.Strong hands-on software development experience.Experience building production-grade automation or AI-powered applications.Experience with LLMs, Generative AI, or Agentic AI technologies.Strong programming skills, particularly in Python or other modern languages.Experience integrating APIs, tools, data sources, and external systems.Understanding of AI agent concepts including tool use, retrieval, planning, memory, context management, and verification.Strong analytical, problem-solving, and scalable system design skills.

Preferred Qualifications

Experience building agentic AI systems or autonomous security workflows.Experience with SOAR, SIEM, security automation, threat intelligence, threat hunting, detection engineering, or incident response.Knowledge of RAG, vector databases, embeddings, semantic search, and knowledge retrieval.Experience with multi-agent architectures, AI orchestration frameworks, and AI evaluation/testing frameworks.Familiarity with Kubernetes, cloud platforms, microservices, APIs, and distributed systems.Experience implementing human-in-the-loop controls and approval workflows.Proven ability to take AI solutions from proof of concept (POC) to production deployment.Understanding of enterprise AI security controls and best practices.

GCS is acting as an Employment Business in relation to this vacancy.

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