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Location: Mount Laurel, NJ (Onsite)
Duration: Contract
Experience: 4+ years

We are seeking a Site Reliability Engineer (SRE) III to support a cutting-edge AI Platform Engineering team responsible for building and maintaining the infrastructure behind enterprise AI and machine learning applications. This is an exciting opportunity to work on large-scale distributed systems, Kubernetes environments, and cloud-native platforms that power next-generation AI solutions.

The ideal candidate has a strong background in cloud infrastructure, Kubernetes, Infrastructure as Code, observability, and automation. Experience supporting production environments at scale is essential.

Design, implement, and support highly available, scalable, and secure cloud infrastructure.

Maintain and improve Kubernetes-based production environments.

Deploy and support AI/ML applications across cloud platforms.

Automate infrastructure provisioning and operational processes using Terraform and scripting.

Build and maintain CI/CD pipelines using GitHub Actions.

Monitor system health and performance using Prometheus, Grafana, Datadog, CloudWatch, Elasticsearch, and logging tools.

Troubleshoot production issues across distributed systems, cloud infrastructure, networking, and containerized applications.

Partner with development teams to improve application reliability, scalability, and performance.

Participate in incident response, root cause analysis, and continuous service improvements.

Support large-scale Kubernetes clusters and cloud-native workloads.

Bachelor's degree in Computer Science or a related technical field (or equivalent experience).

4+ years of experience in Site Reliability Engineering, DevOps, Platform Engineering, or Cloud Infrastructure.

Strong understanding of distributed systems, software design, algorithms, and system performance.

Experience programming or scripting with one or more of the following:

Python

Bash

Go

Java

C/C++

Strong troubleshooting and problem-solving skills.

Excellent communication and collaboration abilities.

AWS (required)

Azure or GCP

Kubernetes (required)

Docker

Amazon EKS

Google GKE/GKS

Terraform (required)

GitHub Actions

CI/CD pipeline automation

Prometheus (required)

Grafana

Datadog

CloudWatch

Elasticsearch

Centralized logging solutions

MySQL

Kafka

Experience supporting AI/ML platforms or machine learning infrastructure.

Experience with GPU-based workloads.

Knowledge of AI model deployment or MLOps.

Experience automating operational processes.

Familiarity with enterprise-scale Kubernetes environments.

Python or Go development experience.

Experience with ETL workflows.

Exposure to AI/ML technologies, LLMs, or agentic AI platforms.

Site Reliability Engineer | SRE | DevOps | Platform Engineer | Kubernetes | AWS | Terraform | Docker | EKS | GKE | GitHub Actions | Prometheus | Grafana | Datadog | CloudWatch | Elasticsearch | Kafka | Python | Bash | Go | Infrastructure as Code | Observability | AI Platform | Machine Learning | Cloud Infrastructure | Distributed Systems

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

Location: Mount Laurel, NJ (Onsite)
Duration: Contract
Experience: 4+ years

We are seeking a Site Reliability Engineer (SRE) III to support a cutting-edge AI Platform Engineering team responsible for building and maintaining the infrastructure behind enterprise AI and machine learning applications. This is an exciting opportunity to work on large-scale distributed systems, Kubernetes environments, and cloud-native platforms that power next-generation AI solutions.

The ideal candidate has a strong background in cloud infrastructure, Kubernetes, Infrastructure as Code, observability, and automation. Experience supporting production environments at scale is essential.

Design, implement, and support highly available, scalable, and secure cloud infrastructure.

Maintain and improve Kubernetes-based production environments.

Deploy and support AI/ML applications across cloud platforms.

Automate infrastructure provisioning and operational processes using Terraform and scripting.

Build and maintain CI/CD pipelines using GitHub Actions.

Monitor system health and performance using Prometheus, Grafana, Datadog, CloudWatch, Elasticsearch, and logging tools.

Troubleshoot production issues across distributed systems, cloud infrastructure, networking, and containerized applications.

Partner with development teams to improve application reliability, scalability, and performance.

Participate in incident response, root cause analysis, and continuous service improvements.

Support large-scale Kubernetes clusters and cloud-native workloads.

Bachelor's degree in Computer Science or a related technical field (or equivalent experience).

4+ years of experience in Site Reliability Engineering, DevOps, Platform Engineering, or Cloud Infrastructure.

Strong understanding of distributed systems, software design, algorithms, and system performance.

Experience programming or scripting with one or more of the following:

Python

Bash

Go

Java

C/C++

Strong troubleshooting and problem-solving skills.

Excellent communication and collaboration abilities.

AWS (required)

Azure or GCP

Kubernetes (required)

Docker

Amazon EKS

Google GKE/GKS

Terraform (required)

GitHub Actions

CI/CD pipeline automation

Prometheus (required)

Grafana

Datadog

CloudWatch

Elasticsearch

Centralized logging solutions

MySQL

Kafka

Experience supporting AI/ML platforms or machine learning infrastructure.

Experience with GPU-based workloads.

Knowledge of AI model deployment or MLOps.

Experience automating operational processes.

Familiarity with enterprise-scale Kubernetes environments.

Python or Go development experience.

Experience with ETL workflows.

Exposure to AI/ML technologies, LLMs, or agentic AI platforms.

Site Reliability Engineer | SRE | DevOps | Platform Engineer | Kubernetes | AWS | Terraform | Docker | EKS | GKE | GitHub Actions | Prometheus | Grafana | Datadog | CloudWatch | Elasticsearch | Kafka | Python | Bash | Go | Infrastructure as Code | Observability | AI Platform | Machine Learning | Cloud Infrastructure | Distributed Systems

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

Are you a MongoDB expert ready to step into a true engineering role? Join a global team modernising a large‑scale database estate and move beyond repetitive DBA work.

Own MongoDB operations end‑to‑end (clusters, sharding, replica sets, backups).

Troubleshoot and resolve complex production issues across L1-L3.

Build automation using Python, Ansible, TDD, Agile.

Improve observability with better monitoring, alerting, and performance insights.

Reduce toil by engineering tools and automation that transform the platform.

Deep MongoDB administration expertise.

Strong experience with Ops Manager and backup tooling.

Solid troubleshooting and production support capability.

SRE fundamentals and an automation‑first mindset.

Hands‑on Python and Ansible experience.

Observability experience (monitoring, alerting, dashboards).

Perfect for Senior DBAs wanting to transition into SRE/Engineering.

~25% of your time spent coding and automating, with more growth ahead.

High‑impact role shaping a global database platform.

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

Step into a high‑impact engineering role where you'll shape the future of Microsoft SQL operations at enterprise scale. As a Database SRE, you'll combine deep SQL Server expertise with modern SRE practices to build a more reliable, automated, and observable database platform for one of the world's largest financial institutions.

Lead SQL Engineering - Solve complex SQL Server 2016-2022 challenges across availability, tuning, performance, and architecture.

Shape the MSSQL SRE practice - Influence standards, patterns, SLIs/SLOs, and operational models for the SQL estate.

Act as the top technical escalation - Provide expert‑level guidance on incidents, root cause, and long‑term fixes.

Drive automation and standardisation - Reduce TOIL through scripting, configuration management, and platform engineering.

Enhance observability - Improve monitoring, alerting, telemetry, and reliability insights across the estate.

Collaborate across engineering - Work with product, engineering, and platform teams to deliver resilient, scalable database services.

Deep Microsoft SQL Server expertise (SQL 2016-2022) across performance tuning, HA/DR, internals, and enterprise‑scale architecture.

Strong SRE mindset - SLIs/SLOs, error budgets, automation‑first thinking, and reliability engineering.

Hands‑on automation skills using PowerShell, T‑SQL, and scripting for migrations, deployments, and operational tooling.

Expertise with configuration management tools such as Chef or Ansible for database server builds and standardisation.

Experience reducing TOIL through simplification, automation, and self‑service patterns.

Ability to influence change across risk, controls, transformation, and digital engineering domains.

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

Location: Glasgow / Knutsford (Hybrid- 2 days a week in office)

Team: 6 UK / 5 India

Environment: Part of a wider multi‑cloud engineering organisation (Azure, AWS, GCP)

Growth: Significant technical development opportunities across cloud engineering, automation, and platform build

We are looking for a hands‑on Azure SRE who can design, build, and automate enterprise‑grade Azure Landing Zones and cloud governance frameworks. This is not an application development role - it is a platform engineering role focused on controls, policies, guardrails, IaC, and DevOps automation.

You will work as part of a global SRE function, collaborating with engineers in the UK and India to deliver secure, scalable, policy‑driven Azure environments.

Azure Landing Zone engineering - build, enhance, and automate enterprise landing zones

Azure governance & controls - develop Azure Policies, RBAC, blueprints, and compliance guardrails

Infrastructure as Code delivery - author and maintain IaC using Bicep or Terraform

DevOps engineering - implement CI/CD pipelines, Git workflows, and automated deployments

Cloud platform reliability - ensure availability, performance, and operational excellence

Cross‑team collaboration - work with multi‑cloud engineering teams to drive standards and best practices

Azure expertise across policies, governance, networking, compute, identity, and platform services

IaC development using Bicep or Terraform (must be able to write code, not just run templates)

CI/CD pipelines using Azure DevOps or GitHub Actions

Git repositories - strong understanding of branching, PRs, code reviews

DevOps mindset - automation‑first, iterative delivery, shift‑left engineering

Strong scripting or development capability (PowerShell, Python, or similar)

Experience working in distributed teams (UK + offshore)

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