Senior Automation Engineer

The position is accountable for raising the level of automation across Falck's digital infrastructure and for the technical direction of that automation agenda. Based in Strategic Initiatives – new established part of Digital Infrastructure & Operations. The role is equally advisory and hands-on, combining advisory technical engagement with the infrastructure product teams with direct, hands-on engineering delivery. It assesses automation maturity and advises the product teams on engineering standards and roadmap direction towards DevOps practices, without dictating those roadmaps. It drives the building of Infrastructure-as-Code, CI/CD pipelines, API integrations and machine learning-supported automation that connect existing infrastructure with digital operations via collaboration with specialized teams. It also evaluates the AI, ML and automation capabilities offered by infrastructure vendors, and technically reviews and tests deliverables from Falck's outsourcing partner, entering into dialogue with the vendor on the best solution.

A key focus is to collaborate effectively with third-party providers and drive results for Falck. These results include increased automation coverage across the in-scope infrastructure domains, infrastructure changes delivered through pipelines rather than manual execution, and documented recommendations that inform architecture and sourcing decisions. Falck has outsourced key infrastructure services, primarily to HCL.

Daily tasks

• Drive Falck's automation initiatives by engaging with the specialised teams within AI, Integration, DevOps Center of Excellence, and all Infrastructure Product Teams - bringing the technical insight needed to identify, shape and progress automation opportunities, rather than delivering every initiative hands-on.
• Advise each team on its automation roadmap and on engineering direction for shared components and integration patterns, assessing automation maturity and identifying gaps, and determining which automations belong in the product way of working versus the technical support way of working - without dictating roadmaps, without line responsibility for the engineers involved, and without acting as Tech Lead across infrastructure as a whole.
• Technically review and test automation deliverables produced by HCL, Falck's outsourced infrastructure services partner, and enter into dialogue with HCL to agree the best solution design and implementation approach.
• Deliver hands-on automation that connect infrastructure domains and replace manual operational steps.
• Design modern CI/CD and Infrastructure as Code architecture by building GitOps-based deployment pipelines and implementing Terraform and Ansible solutions, with GitHub Actions as the pipeline engine and AI-supported tooling such as Azure, Claude, and Copilot Studio.
• Enable machine-learning-supported automation by building or create requirements for the data pipelines and telemetry analysis behind predictive alerting and automated anomaly detection, and by operating the full MLOps lifecycle for models in production.
• Support the work to automate operational workflows through platform APIs by streamlining workflows, asset records, incident and change processes, and service delivery reporting, primarily in ServiceNow.
• Evaluate emerging technologies and vendor capabilities by benchmarking and running proofs of concept on AI, ML, and automation features embedded in infrastructure tooling, and documenting recommendations

Requirements

Bachelor's or Master's degree in computer science, software engineering, IT engineering or a comparable field, or equivalent documented practical experience Minimum 3 years in infrastructure engineering, systems architecture or DevOps, with a demonstrated transition into the AI space (for example LLM-based tooling and automation). Documented record of guiding teams through automation transformation programmes, in a technical lead or equivalent role. Working knowledge of Infrastructure-as-Code tools (Terraform, Ansible) and of CI/CD platforms; hands-on delivery experience is preferred. Experience with GitHub, Claude, and Copilot Studio. Programming and scripting in Python, which is required for the ML and automation work, and in Go, Bash or PowerShell. Familiarity with API-driven automation of network fabric, firewalls and IAM protocols (OAuth, SAML, Active Directory); hands-on experience with API integrations is not required, though knowledge is an advantage. ITSM and process automation through platform APIs, primarily ServiceNow: workflows, asset tracking, incident and change loops, service delivery metrics. Jira Service Management is an advantage. ML fundamentals, MLOps, and telemetry data analysis – log aggregation and AIOps. Enterprise cloud architecture on Azure, and containerisation and orchestration with Docker and Kubernetes. Experience with GCP is not required. Advising on technical direction and standards for engineers outside own reporting line, without formal authority over them. Advantage: work within a centralised strategy, architecture or Center of Excellence team structure. Advantage: automation within ITIL, asset management or vendor service delivery frameworks. .Interpersonal relations: consultative engagement with all Infrastructure Product Teams - including Project & Process Management - and with HCL, establishing agreement on shared standards without formal authority. Technical leadership: ability to advise on design decisions and encourage adoption of defined standards through code review, and to reach technical agreement across teams as an advisor rather than as Tech Lead across infrastructure as a whole. Analytic analysis: assessment of automation maturity, telemetry data and vendor capability against enterprise requirements. Flexibility: equal movement between advisory technical leadership and own hands-on code delivery, and adaptation to differing maturity levels across teams. Multitasking: prioritisation across parallel product teams, initiatives and Proofs of Concept. IT knowledge: infrastructure engineering, Infrastructure-as-Code, GitOps practice and machine learning applied to infrastructure operations. Communication: technical documentation of standards and decisions, and presentation of recommendations to technical and non-technical stakeholders in English. Knowledge transfer: coaching, pair programming and code review.

Must have: Python