Zartis

• Design and build robust backend services using TypeScript and NestJS • Work with Prisma and AWS to build scalable, production-grade systems • Incorporate AI tooling and prompt engineering into development workflows • Contribute to architectural decisions and technical standards • Help shape AI-assisted or spec-driven development practices • Collaborate closely with stakeholders across engineering and product.

• Lead the evaluation and implementation of an API gateway solution for the platform • Consolidate existing pipelines and create a blueprint covering security standards and best practices • Apply and transfer API gateway knowledge across cloud providers (AWS, Azure, GCP) • Contribute to building and operating shared platform capabilities for application development teams

• Build and operate secure agent runtimes with sandboxing, runtime isolation, network policies, secrets management, RBAC, and approval flows that make agents a credible part of the infrastructure. • Design and maintain the integration surface with MCP-style adapters and gateways that let agents act on source control, CI/CD, ticketing, documentation, cloud, and observability systems across all marketplace teams. • Build and own the evaluation pipeline with golden tasks, graders, regression tests, and release gates that make agentic workflow correctness measurable and cheap enough that teams actually use it. • Implement observability and cost control including traces, telemetry, token usage, cost-per-workflow, rate limits, and failure handling so stakeholders always know what is running, what it costs, and what to do when it breaks. • Create reusable scaffolding including templates, starter kits, wrapper scripts, and workflow automation that turn proven patterns from marketplace pilots into platform components every team can adopt in a day. • Partner with the AI Architect to make the reference architecture real, in code, in production, on a schedule that does not slip.

• Contributing to the definition of the Test Automation architecture • Owner of the common (test automation) framework components and API/MNO simulation systems • Promote standardization of test automation practices across the Technical organisation • Providing guidance and technical support on Test Automation framework use to scrum teams • Training testers and developers on the use of test automation framework and tools • Provide Test Automation support to the UAT team • Evaluating and piloting the introduction of new test automation technologies, practices and approaches • Designing and developing Common Framework components • Source (oracle) of knowledge on test automation • Recruitment: Evaluating test automation capabilities of potential test and software engineering candidates • From time to time the Test Automation Analyst may be attached to scrum teams to carry out work such as setting up new frameworks and test execution pipelines • They will also be involved in PI planning sessions as a test automation consultant and from time to time may be required to support the performance test team

• Build and enhance web-based BI and analytics applications using Angular or similar frontend frameworks. • Write and work with complex, production-grade SQL queries that power business logic and reporting workflows. • Develop and iterate on user-facing product features across frontend and data-driven applications. • Translate business requirements and data logic into intuitive, scalable user experiences. • Collaborate closely with stakeholders to understand metrics, reporting needs, and operational workflows. • Contribute to modular and scalable frontend architectures, including micro-frontend environments where applicable. • Work across both frontend and data layers, contributing to end-to-end product delivery. • Take ownership of solutions — from frontend implementation and data logic to production delivery. • Ensure production-ready systems with a focus on maintainability, usability, and clean code. • Work in a fast-paced, evolving environment where requirements and priorities can shift quickly.

• Build and extend multi-agent systems and agentic workflows using frameworks such as AWS Agent Core and AWS Bedrock Flows (or equivalent orchestration tools). • Develop and integrate Retrieval-Augmented Generation (RAG) pipelines for internal tools. • Implement LLM-powered chatbots, assistants, and autonomous agents tailored to specific business use cases. • Collaborate closely with the Team Lead to understand requirements and translate them into reliable, scalable implementations. • Take existing proof-of-concept or in-progress AI systems and harden them to production-grade standards. • Pipeline AI components together within the AWS and Databricks ecosystem, ensuring reliable end-to-end data and model workflows. • Apply best practices in observability, logging, and monitoring for deployed AI systems. • Contribute to CI/CD processes for model and prompt deployment where applicable. • Mentor and support other engineers within AI. • Communicate progress, blockers, and technical decisions clearly to both technical and non-technical stakeholders. • Participate in technical discussions and contribute to architectural decisions for AI systems.

• Designing and delivering scalable frontend features using TypeScript and React for large-scale applications used by both customers and internal teams. • Taking ownership of features from discovery through to release, contributing to architectural decisions and evolving patterns as the codebase grows. • Building shared components and tooling while writing well-tested, high-quality code. • Collaborating with product managers, designers, and backend engineers to shape intuitive user experiences on top of complex systems. • Continuously improving performance, scalability, and overall quality across the platform.

• Build and maintain strong, long-lasting relationships with assigned digital clients, consistently holding yourself to the highest standards of service. • Support account retention and help identify opportunities for account growth. • Respond with agility and accuracy to client needs and issues, collaborating with internal stakeholders to deliver timely solutions. • Monitor client satisfaction and engagement through regular interactions with clients and engineering teams, proactively identifying and addressing potential challenges. • Efficiently prioritize your time to align with essential client goals and activities.

• Build relationships and collaborate with Heads, Tech Partners, and Tech Heroes to understand hiring needs and team goals. • Be an active member of the hiring team for all digital projects, working on a variety of roles ranging from engineering, product, and more. • Manage the full cycle hiring process, from sourcing (with support from Tech Sourcers) to closing, ensuring a smooth and positive candidate experience. • Comply with all relevant standards, policies, and procedures, both internally and externally, such as GDPR and ISO. • Support Tech Sourcers when it comes to best sourcing practices and methods. • Represent Zartis to the highest standard to strengthen the Zartis brand and candidate experience.

• Design and implement scalable data models and pipelines on Snowflake using Snowpark and SQL • Write complex, production-grade SQL (dbt models, views, UDFs) to power business logic and product features • Build data-facing application layers using Streamlit (in Snowflake) or similar frameworks • Develop and iterate on greenfield product features across AI Pod and Rights360 platforms • Create user-facing applications on Snowflake, with potential extension into lightweight APIs (e.g. FastAPI) • Leverage Snowflake Cortex AI/ML services for forecasting, profitability modelling, and conversational/agentic features • Contribute to real-time inventory management and rights conflict detection (Rights360) • Build conversational interfaces enabling natural language data querying for operational teams • Collaborate closely with the shared tech lead across multiple workstreams • Take end-to-end ownership of solutions — from data modelling and logic to UI delivery • Ensure production-ready systems with a focus on reliability, maintainability, and clean code • Work across the full stack, from data pipelines to user-facing dashboards