Senior DevOps Engineer

Join AutogenAI – Revolutionising Bid and Proposal Writing with generative AI 

AutogenAI is a leader in Generative AI SaaS, transforming how organisations create and optimize winning tenders and proposals through cutting-edge natural language processing technology. We are one of the fastest-growing companies in the industry, expanding rapidly to meet the increasing demand for AI-driven solutions across sectors. 

Our innovation stems from a belief that language technology will revolutionise business communication over the next decade. We empower our clients to grow faster and more efficiently by delivering bespoke AI models tailored to their needs, saving time, improving content quality, and boosting win rates in highly competitive markets. 

We drive AutogenAI’s growth by fostering a culture where innovation and ambition thrive, building a company where everyone can have a career-defining experience. As we scale, we invite passionate professionals to join our journey of innovation, helping shape the future of AI-powered business solutions. 

Job summary:

As a Senior DevOps Engineer at AutogenAI, you will play a crucial role in designing, deploying, and optimizing our infrastructure to support fast and reliable delivery of new features. You will lead initiatives around Kubernetes deployment, CI/CD pipeline development, and system reliability, ensuring that our systems are always ready to scale. This role offers the unique opportunity to shape the DevOps culture within a high-growth environment, collaborating across engineering teams to drive process improvements and resilience. 

What you'll be responsible for:

• Service Deployment & Management: Implementing and managing services across multiple environments (AWS, Azure, proprietary cloud) using Kubernetes to ensure scalability and reliability. 

• Automation & Reliability: Building and maintaining CI/CD pipelines to streamline deployments, enhance monitoring, and support efficient recovery processes. 

• Cross-Functional Collaboration: Partnering with cross-functional teams to ensure the seamless deployment and operation of software solutions. 

• Engineering Standards & Culture: Shaping engineering standards, tooling, and processes through code reviews, collaborative development, and post-mortems to strengthen our DevOps culture. 

• Issue Resolution: Troubleshooting and resolving production issues, ensuring high system availability and reliability. 

• Emergency Readiness: Being available for on-call support in emergency situations (rarely needed) to maintain uninterrupted service continuity. 

What you'll bring to the team:

• Technical Expertise: Extensive experience in cloud development and Kubernetes deployment, ensuring our systems are robust and scalable. 

• Problem-Solving Skills: Proven capability to diagnose and resolve production issues quickly, ensuring minimal downtime. 

• Communication Skills: Strong communication abilities, enabling you to work closely with cross-functional teams and provide clarity in complex technical discussions. 

• Adaptability and Initiative: Enthusiastic about taking on new challenges outside of DevOps to support our fast-growing and evolving environment. 

• Experience: 5+ years in DevOps or platform-related roles with a focus on Kubernetes, CI/CD, monitoring, and scaling. 

• Technical Skills: Proficiency in managing cloud infrastructure across AWS, Azure, and proprietary environments; hands-on experience with Kubernetes and CI/CD tools. 

• Industry Knowledge: Familiarity with production systems, recovery processes, and modern DevOps practices. 

• Security Clearance Eligibility: Willingness to undergo national security vetting to at least BPSS level, as this role includes systems access to sensitive data. 

Preferred qualifications:

• Database Optimisation: Experience diagnosing and resolving performance issues with databases and other infrastructure services. 

• Secure Multi-Account Infrastructure: Proficiency in managing AWS multi-account setups, preferably using Control Tower. 

• Client Deployment Management: Experience with managing client-owned deployments of software. 

• AI and ML Infrastructure: Familiarity with AI-powered online services and infrastructure for machine learning (ML) and large language models (LLMs).