Sr. DevOps Engineer

We are looking for a senior DevOps professional who owns the platforms, automation, and operational practices that let engineering teams ship software safely, quickly, and reliably. This is a senior individual contributor who is accountable for reducing lead time for changes, improving production reliability, and cutting operational toil through engineering guardrails rather than manual effort.

The ideal person leads delivery of CI/CD and infrastructure-as-code end to end, reasons through architectural trade-offs, and stays calm while debugging production incidents. In 2026 the mandate has grown to include AI-assisted operations — introducing agentic automation and AIOps into the delivery lifecycle, where systems reason over operational signals and take action rather than just surface dashboards.

The value this person brings is faster, more reliable delivery at lower operational cost, with modern AI capabilities folded into the toolchain as a first-class capability.

We are seeking a hands-on senior engineer with a strong ownership mindset — someone who has grown beyond executing tickets into shaping how a team delivers software. They are comfortable being the person other engineers turn to during a difficult release or a production incident, and they lead by example rather than title.

This is a senior individual-contributor profile that partners closely with software engineering, reliability, security, and cloud teams. It suits someone open to a remote engagement or to on-site deployment with mobilization to the Middle East, Europe, or North America, depending on the client. The person we want is pragmatic, automation-minded, and motivated by making delivery smoother for everyone around them.

A strong candidate for this role is someone who has already owned delivery pipelines end to end and has felt the consequences of a fragile release process — and built their way out of it. They bring a track record of turning manual, error-prone operations into automated, observable, and safe systems, and they can point to real incidents they led and real toil they removed. On top of that engineering foundation, we want someone curious about applying AI to operations in a controlled, sensible way.

In practice, the responsibilities break down as follows:

• Delivery pipelines: Design, build, and operate CI/CD pipelines that automate build, test, and release so changes ship reliably and often. Make every risky change traceable, limit its blast radius, and ensure a clear recovery path.
• Infrastructure & cloud: Own infrastructure-as-code (provisioning, configuration, drift control) with safe change discipline; manage containerization and orchestration, including rollout strategy and hardening.
• Reliability & incident response: Lead incident response and blameless post-incident improvement; establish observability and guardrails that keep deployments both fast and safe.
• Cost & security: Own cloud cost posture and security-by-default in pipelines (shift-left controls, supply-chain integrity, policy-as-code).
• Mentor mid-level engineers and set delivery standards; introduce and operate AIOps and agentic automation within the delivery lifecycle.

We want to see an engineer who is genuinely fluent in modern delivery tooling and who treats automation as the default rather than the exception. They should be able to move comfortably across pipelines, infrastructure, and cloud, and be equally at home diagnosing a failed deployment as designing a new one. Just as important, we are looking for someone leaning into the shift toward AI-assisted operations — not as a buzzword, but as a practical way to reduce toil and respond faster, applied with appropriate guardrails.

The following are the areas of expertise we expect to see, at varying depths:

Core DevOps

• CI/CD pipeline design and release automation.
• Infrastructure-as-Code with Ansible, HashiCorp Terraform, CloudFormation and/or equivalent.
• Cloud on AWS or equivalent (cloud-agnostic); containerization and orchestration; multi-environment promotion.
• Observability, SLOs, and reliability engineering.

Delivery performance

• Familiarity with delivery-health metrics (deployment frequency, lead time for changes, change failure rate, time to recovery) and the discipline to move throughput and stability together.

Modern Agentic AI / Bedrock / AIOps *(niche areas we are seeking — depth explored at interview)*

This role is delivered through Solutions Chapter Group's Human Resources chapter (Chapter 12) as a Recruitment Process Outsourcing (RPO) engagement, under our Technical Recruitment stream. Rather than a "post-and-pray" marketplace approach, we use a Curated Professional Recruitment model: candidate profiles are pre-vetted in our internal database, and when a required profile isn't already available, our dedicated Scout network conducts global headhunting to secure it. We screen and match candidates against each client's specific requirements, and placements may be remote or an on-site deployment with mobilization to the Middle East, Europe, or the United States.

From a recruitment-fit perspective, we screen for:

• Strong ownership and a bias toward automation over manual effort.
• Ability to reason through trade-offs and explain *why*, not just *what*.
• Clear cross-team communication and the ability to set and hold delivery standards.
• Mentorship instincts and calm leadership under production pressure.
• Openness to the engagement model (remote or mobilized on-site) and readiness for cross-region deployment.

Areas to explore at interview *(topics only)*

• Pipeline ownership and safe change practices

CI/CD, Infrastructure-as-Code (Terraform), AWS, Kubernetes, observability/SRE, DORA metrics

Bachelor's degree in Computer Science or equivalent practical experience