• Designing, building, and operating VP's backend services, including the orchestration engine and the automated decisioning pipeline, with a strong focus on reliability, scalability, and maintainability • Delivering key orchestration features such as multi-method flow execution, branching and fallback logic, and webhook integrations • Improving the resilience of production-critical systems — backpressure and idempotency handling, backwards-compatibility testing, SPOF elimination, and end-to-end monitoring • Participating in on-call rotations, incident response, and postmortems to ensure our most critical flows stay healthy • Driving engineering quality through code reviews, CI practices, runbook documentation, and mentoring teammates

• Helping to build Cytora’s Underwriting Productivity Suite, a serverless based web application that increases efficiency and effectiveness of underwriters • Joining the platform team, responsible for the infrastructure of our application, our monitoring systems and our CI/CD pipelines

• Architecting systems that scale with the business. • Raising engineering quality and operational excellence. • Accelerating development velocity through effective use of AI. • Establishing best practices for AI-assisted and agentic software development. • Mentoring engineers and helping the team make better technical decisions. • Leveraging technology to simplify complex operational workflows and improve customer experiences. • Define and evolve architectural standards across customer-facing and operational systems. • Lead the design of complex software systems, integrations, workflows, and data models. • Drive long-term technical strategy while balancing short-term business priorities. • Identify technical risks and opportunities early and develop pragmatic plans to address them. • Lead architectural reviews and guide major technical decisions across teams. • Establish patterns that improve reliability, maintainability, scalability, and developer productivity. • Champion AI-assisted software development across the organization. • Define best practices for leveraging LLMs in coding, testing, debugging, documentation, code review, and operational workflows. • Design and build agentic systems that automate engineering and business processes. • Evaluate emerging AI technologies and determine where they can create measurable value. • Help iterate on Koala's approach to AI-enabled software development and organizational productivity. • Ensure AI systems are implemented responsibly, securely, and with appropriate operational safeguards. • Raise the bar for code quality, testing, documentation, and operational readiness. • Drive improvements in CI/CD, deployment safety, developer experience, and engineering workflows. • Establish standards for observability, monitoring, alerting, and incident response. • Introduce tooling and automation that improve engineering velocity without sacrificing quality. • Foster a culture of ownership, continuous improvement, and technical excellence. • Partner closely with Product, Operations, Pharmacy, Customer Care, Growth, and Finance teams to understand business challenges and design effective solutions. • Translate ambiguous business requirements into scalable technical approaches. • Lead initiatives from concept through implementation, rollout, and operational support. • Ensure technical decisions align with company goals and customer outcomes. • Help mentor engineers across all experience levels. • Provide thoughtful guidance through design reviews, architecture discussions, and code reviews. • Help develop engineering processes that scale as the organization grows. • Serve as a trusted technical advisor to cross-functional stakeholders. • Influence engineering culture through technical leadership rather than organizational authority.

• Investigation & Root Cause Analysis Own end-to-end investigation of ad-hoc technical issues raised by product, operations, or engineering teams. • Diagnose data integrity problems by tracing issues across event streams, APIs, and database layers. • Analyse Kafka event histories to reconstruct system state and identify where data diverged from expected behaviour. • Produce clear root cause analysis (RCA) documentation that explains what happened, why, and how to prevent recurrence. • Data Analysis & Resolution Write complex SQL queries against production and staging databases to investigate data anomalies, gaps, and inconsistencies. • Validate proposed fixes in lower environments before escalating to production resolution recommendations. • Use REST APIs to probe system state, trigger reprocessing workflows, and verify expected outputs. • Collaborate closely with software engineers to understand system internals and escalate findings with sufficient context for developers to act. • Produce concise, structured investigation reports suitable for both technical and non-technical audiences. • Maintain a knowledge base of known issues, recurring patterns, and resolution playbooks.