Senior DevOps Engineer (AI) at Bilue

Sydney, New South Wales, Australia -

Full Time

Start Date

Immediate

Expiry Date

26 Aug, 26

Salary

0.0

Posted On

28 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AWS, Kubernetes, Terraform, CI/CD, LLMOps, Python, Docker, Infrastructure as Code, Prometheus, Grafana, Datadog, ELK Stack, Linux Administration, SRE, CloudFormation, Bash

Industry

IT Services and IT Consulting

Description

Company Description Bilue is a digital consultancy that designs and builds smart, user-friendly technology for some of Australia’s most well-known businesses. From mobile apps to beautifully designed web platforms and digital experiences, we create solutions that drive impact and deliver exceptional customer outcomes. Our culture is people-first and purpose-driven. We’re a down-to-earth, values-led team with offices in Sydney and Melbourne, and a growing presence in Manila. We genuinely enjoy working together, whether we’re solving tough tech problems, brainstorming creative solutions, or grabbing a coffee between meetings. Curiosity is encouraged. Collaboration is second nature. We value excellence, not ego, and back each other to do great work without micromanagement. With low politics and high trust, it’s a place where delivery people, designers, and engineers genuinely connect, and where everyone has a voice, space to grow, and a little fun along the way. Job Description We're looking for a Senior DevOps Engineer to join our Applied AI practice and work at the intersection of platform engineering and AI delivery. This is a hands-on role where you'll lead the optimisation and evolution of our cloud infrastructure, deployment pipelines, and operational practices to ensure we consistently deliver high-quality outcomes for our clients. This isn't a standard DevOps role. You'll be building and operating the infrastructure that production AI systems actually run on, agentic pipelines, LLM integrations, retrieval systems, in enterprise environments across financial services, government, insurance, and retail. That means bringing the same rigour you'd apply to any critical system, and then going further: LLMOps, inference cost engineering, evaluation harnesses, and resilience patterns purpose-built for non-deterministic APIs. You'll work closely with AI Engineers, delivery teams, and client stakeholders to uplift platform capability, improve delivery velocity, and embed quality through automation, observability, and strong engineering standards. Core DevOps Architect, build, and continuously enhance CI/CD pipelines to automate and accelerate software delivery across the team. Lead the management and optimisation of cloud infrastructure (AWS), ensuring scalability, security, and reliability while championing best practices. Design, implement, and maintain Infrastructure as Code (IaC) with tools such as Terraform and CloudFormation, enabling the team to deploy with confidence and agility. Proactively monitor, troubleshoot, and enhance system performance, availability, and security, ensuring operational excellence across client environments. Drive the adoption of containerisation and orchestration technologies like Docker and Kubernetes to enable scalable, high-performance solutions. Improve system observability by implementing advanced logging, monitoring, and alerting with tools such as Prometheus, Grafana, Datadog, CloudWatch and the ELK stack. Lead the implementation of security best practices, including IAM, secrets management, and vulnerability assessments. Collaborate closely with developers to continuously optimise build, deployment, and scaling strategies for seamless integration and continuous delivery. Automate key operational tasks and apply SRE principles to enhance system reliability, uptime, and overall performance. Take ownership of incident response and lead root cause analysis for production issues, ensuring swift resolution and ongoing improvement. AI-Specific Responsibilities Practise LLMOps: implement prompt versioning, model evaluation pipelines, and controlled promotion gates before anything reaches production. Instrument beyond standard metrics: design observability for token costs, inference latency, retrieval quality, and model drift detection. Build agentic resilience: implement rate limiting, circuit breakers, and graceful fallbacks for non-deterministic LLM APIs. Own inference cost engineering: design throughput management, caching strategy, and cost-per-query alerting to keep AI systems economically viable at scale. Design AI-native CI/CD pipelines with evaluation harnesses and golden dataset regression tests baked in before any model or prompt change reaches production. Qualifications 5+ years of hands-on experience in DevOps, SRE, or Cloud Engineering. Extensive expertise in AWS cloud platforms and services. Practical experience with Kubernetes and containerisation technologies. Strong scripting and automation skills with Bash, Python, or Go. In-depth knowledge of CI/CD tools including Jenkins, GitHub Actions, GitLab CI/CD, and ArgoCD. Solid experience with Infrastructure as Code tools including Terraform and CloudFormation. Comprehensive understanding of Linux administration and networking fundamentals. Experience implementing security best practices including IAM, SSL/TLS, and compliance frameworks such as SOC2, ISO 27001, and GDPR. Proficiency in monitoring and logging tools including the ELK Stack, Prometheus, Grafana, or Datadog. Exceptional problem-solving skills and the ability to operate in a fast-moving, ambiguous environment. Strong communication and collaboration skills to work effectively across cross-functional teams, including client stakeholders. Nice to Have Familiarity with serverless architectures such as AWS Lambda. Experience with database performance tuning and scaling techniques. Relevant certifications in AWS, Azure, or GCP DevOps. Prior experience supporting AI or ML workloads in production environments. Familiarity with LLM observability tooling such as LangSmith, Weave, or similar. Additional Information Life at Bilue People-first focus: We’re committed to delivering exceptional outcomes for our clients, but we know it starts with our people. You’ll join a values-led team that’s collaborative, curious, and genuinely cares about doing great work, together. Connection that counts: From monthly anchor days and team lunches to our annual offsite, we create intentional moments to connect, collaborate, and celebrate. These aren’t just fun perks, they’re part of how we work and grow together. Flexibility that works: We offer hybrid working, with minimum 3 days per week in the office. It’s a balance that gives you the space to do your best work, while still creating time to connect and build strong relationships in person. Strong internal communities: We actively foster internal communities across tech, design, delivery, and beyond, giving you plenty of chances to connect, share knowledge, and learn from your peers. Opportunities to grow: We invest in your development with unlimited access to Go1’s learning library and support from our internal performance coach. Whether you want to deepen your technical skills or grow your leadership potential, we’ll back you. Flat structure, real impact: At Bilue, everyone’s voice matters. Our leadership team is hands-on and approachable, and we operate without unnecessary layers. We keep things open and transparent, and your ideas will be heard, no matter your title. Bilue = Big + Blue Ocean. Are you ready to set sail? Apply now! NB. This is a full-time position based in Sydney. To be considered, candidates must have unrestricted working rights in Australia.

Responsibilities

Lead the optimization of cloud infrastructure and CI/CD pipelines to support production AI systems and agentic pipelines. Implement LLMOps practices, including inference cost engineering, model evaluation, and observability for non-deterministic APIs.