• Lead the design and development of complex features and components for our cloud-based SaaS platform. • Architect and implement scalable solutions, provide technical guidance to other engineers, and contribute to the evolution of our technology stack. • Take on greater technical responsibility and ownership. • Work as part of a collaborative full-stack engineering team and report directly to the Software Engineering Team Lead in the UK, bringing strong technical ownership, sound judgment, and a pragmatic approach to building reliable systems.

• Design, build, and maintain end-to-end product features across frontend, backend, and AI services • Develop AI-powered capabilities such as recommendations, automation, summarization, classification, or decision support • Integrate LLMs and ML models into production systems with attention to performance, reliability, and cost • Build and consume well-designed APIs and services that support scalable AI workflows • Collaborate closely with Product Managers, Designers, and Data/ML partners to translate business problems into technical solutions • Ensure high code quality through testing, reviews, and adherence to engineering best practices • Debug and resolve complex issues across the stack, including data, model behavior, and user experience • Contribute to improving engineering standards, tooling, and developer experience within the team

• Partner with stakeholders to analyze requirements, ensuring clarity, feasibility, and alignment with product strategy. • Assess proposed business needs for technical suitability, architectural impact, and long-term maintainability. • Translate functional requirements into technical designs, architectural concepts, and implementation plans. • Actively contribute to the codebase, including designing, implementing, reviewing, and optimizing software components. • Provide hands-on technical guidance to engineering teams, ensuring consistent execution, adherence to standards, and high-quality delivery. • Communicate complex technical topics in a clear and structured manner to both technical and non-technical audiences. • Support cross-team alignment and contribute to the definition and evolution of architectural patterns and best practices. • Mentor engineers and support talent development within the organization.

• Lead development teams to ensure sprint commitments are met • Define and maintain AI technical standards, reference architectures, prompt libraries, templates, and playbooks • Partner with sales and delivery to design AI strategies, architectures, and proof of concepts • Architect and deploy MLOps/AIOps platforms that support model lifecycle management, evaluation, and monitoring • Develop and deliver AI training programs, workshops, and internal documentation