Apply Digital

Solutions Engineer

• Define, own, and evolve the high-level technical architecture for internal and client platforms and shared services, ensuring systems are scalable, secure, observable, and production-ready.
• Organizing, distributing and translating backlog requirements from Product, UX and other disciplines, into detailed spec driven requirements for Agents to implement.
• Synthesize user stories, site maps, content strategy, components and design systems, brand strategy, etc, into specifications that coding Agents will implement.
• Designing and implementing digital solutions that have proper SEO/GEO, accessibility, performance and content management integrations.
• Integrations with key Composable platforms such as Contentful, Contentstack, Algolia, Cloudinary, etc.
• Champion spec-driven development as a core practice to improve clarity, quality, and predictability across teams.
• Design and guide layered and distributed architectures, ensuring sound use of queues, caching, APIs, and database schemas while using teams of coding agents.
• Establish standards for creating and consuming RESTful APIs across services.
• Coach engineers on effective agent design, prompt architecture, and decision modeling.
• Translate business goals into agent capabilities and system-level behaviours.
• Define when autonomy is appropriate vs. when human oversight is required.
• Lead the design and implementation of AI-powered systems, including: LLM integrations (Gemini 3, Claude Opus, GPT-4.x/5.x); Vector stores and Retrieval-Augmented Generation (RAG) pipelines.
• Set direction for agent observability, debugging, and reliability in production environments.
• Embed AI coding agents (Copilot, Claude Code, etc.) into development workflows to improve velocity, quality, and developer experience.
• Continuously evaluate and introduce new AI tools and techniques to accelerate delivery while maintaining enterprise standards.
• Promote disciplined experimentation and learning around emerging AI capabilities.
• Provide technical leadership for systems built on Google Cloud Platform (GCP).
• Oversee infrastructure design and provisioning, with Terraform as a preferred approach.
• Ensure systems meet expectations for reliability, scalability, and operational excellence.
• Lead and mentor senior engineers and technical leads across multiple teams.
• Foster a calm, supportive, and solution-oriented engineering culture.
• Partner with Engineering Managers, Product, and Delivery leaders to align technical initiatives with organizational goals.
• Manage dependencies and technical risks across concurrent initiatives.
• Identify and mitigate technical, architectural, and delivery risks early.
• Drive continuous improvement in how software is designed, built, tested, and operated, especially through AI-enabled practices.
• Ensure systems and teams are prepared for long-term maintainability and evolution.

Solution Architect, Agentic Engineering

Frontend Engineer

• Lead the design and development of high-performance frontend applications using TypeScript, React, and Next.js.
• Organizing, distributing and translating backlog requirements from Product, UX and other disciplines, into detailed spec driven requirements for Agents to implement.
• Synthesise user stories, site maps, content strategy, components and design systems, brand strategy, etc, into specifications that coding Agents will implement.
• Designing and implementing digital solutions that have proper SEO/GEO, accessibility, performance and content management integrations.
• Integrations with key Composable platforms such as Contentful, Contentstack, Algolia, Cloudinary, etc.
• Experience implementing enterprise grade design systems, content models and component libraries.
• Apply spec-driven development to ensure clarity, consistency, and high-quality delivery.
• Architect frontend solutions that integrate seamlessly with backend services and AI-powered systems.
• Design user experiences that help users express goals, constraints, and context clearly to AI agents.
• Design and implement frontend experiences that leverage: AI-powered APIs and LLM-driven features and RAG-based experiences and AI-assisted workflows.
• Collaborate with backend teams to consume RESTful APIs effectively.
• Ensure frontend systems are scalable, maintainable, accessible, and well-documented.
• Provide mentorship and technical leadership to frontend engineers.
• Partner with Project Managers and stakeholders to manage delivery risks and timelines.
• Communicate complex frontend and AI concepts clearly to technical and non-technical audiences, including clients.

Principal Agentic Engineer – Front-end

Backend Engineer

• Lead the design and development of scalable, secure, and high-performance backend systems using Python and modern cloud-native patterns.
• Apply spec-driven development practices to ensure clarity, quality, and predictable delivery.
• Organizing, distributing and translating backlog requirements from Product, UX and other disciplines, into detailed spec driven requirements for Agents to implement.
• Coordinate teams of coding agents to deliver engineering requirements.
• Design and implement RESTful APIs to support frontend, mobile, and third-party integrations.
• Architect and deliver AI-powered backend solutions, including: Vector stores and Retrieval-Augmented Generation (RAG) pipelines, integration with LLMs (e.g., Gemini, Claude, GPT-4/5), and use of AI coding agents and developer copilots to improve delivery velocity.
• Develop and maintain systems using Google Cloud Platform (GCP), with hands-on experience in, Vertex AI, Google Gen AI APIs.
• Leverage Agent Development Kits (ADKs) (e.g., Google ADK) to design and implement intelligent agent-based systems.
• Ensure systems are observable, reliable, and debuggable in production environments.
• Collaborate with engineers to design well-architected, maintainable solutions aligned with business goals.
• Mentor and guide engineers, fostering technical excellence and continuous learning.
• Partner with Project Managers and cross-functional teams to manage delivery risks and timelines.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders, including clients.

Principal Agentic Engineer – Back-end

Artificial Intelligence

• Act as the AI, LLM, and Data Science SME on client engagements, supporting discovery, solution design, and delivery activities.
• Lead technical discussions with client stakeholders to assess AI readiness, data availability, architectural considerations, and feasibility.
• Design and guide AI solution approaches, including: Large language model–based applications (e.g., retrieval-augmented generation, orchestration, evaluation). Applied machine learning and data science workflows. Integration with enterprise data platforms and digital systems.
• Collaborate with data engineers, platform engineers, and application teams to ensure AI solutions align with cloud-native architectures and delivery standards.
• Support the progression of AI initiatives from early experimentation into implementation phases suitable for broader organizational adoption.
• Advise on evaluation, monitoring, and operational considerations for AI and machine learning solutions.
• Embed responsible AI, privacy, security, and compliance considerations into solution design and delivery.
• Partner with cross foundational teams to support proposals, discovery workshops, and active client engagements.
• Contribute to reusable AI patterns, approaches, and documentation that can be leveraged across multiple clients.
• Stay current with emerging AI, LLM, and data science techniques, applying new capabilities where they provide clear value.

Director of AI

Project Manager

• Effective project management of all assigned project resources, ensuring all deadlines are met with an accurate and high-quality product.
• Provide assistance to the Customer Success Manager who is responsible for guiding the client through the support process. This role will customize the deliverables and dates according to the specific project, and effectively manage all deliverables and communications with the Customer Success Manager and sometimes the client.
• Participate in all internal meetings, ensuring all client requests are ticketed and contain sufficient information, as well as provide answers to any questions from other internal team members.
• Track all tasks in our project management tool, and partner with our internal team to ensure sufficient resourcing and on-time delivery of assets.
• Identify any roadblocks that prevent a project from being delivered on time. Partner with our internal team to determine how to remove roadblocks.

Project Coordinator

Sales Engineer

• Support business development efforts in providing scoping and solutioning aligned to our products and services, and packaged to be a clear deliverable
• Support in transitioning newly signed clients to the delivery team, providing clarity into discussions and decisions that were made during the sales process, and guidance to the internal team on key milestones
• Travel for and attend conferences, partner events, client on-sites, and prospect pitches.

Copywriter

• In-depth knowledge of mobile-first, responsive design elements to be able to understand how your copy will be executed in an email
• Assisting in the conception of new campaigns
• Produce copy based on briefs submitted by clients
• Critical review of strategic briefs before executions
• Collaborate with strategy, creative, and dev teams to ensure emails not only look great but function great
• Attend internal and client-facing meetings
• Incorporate client feedback into revisions
• Excellent copy editing skills to ensure it's free of errors and that it adheres to brand guidelines
• Match brand voice so flawlessly, that the reader can’t tell if an agency or a brand’s creative director wrote it

Freelance Copywriter

Analytics Engineer

• Are you passionate about transforming raw data into clean, trusted, and insightful datasets that empower business teams to make smarter decisions?
• Do you thrive in fast-paced environments where collaboration, data storytelling, and scalable analytics workflows are essential?
• Are you excited to work cross-functionally with marketers, product teams, and UX designers to deliver end-to-end analytics solutions—from event tracking implementation to self-serve dashboards?
• As a Senior Analytics Engineer, you will play a critical role in designing, modeling, and transforming data to support actionable insights across our Composable digital platforms.
• You’ll build and maintain scalable dbt models, optimize semantic layers, and ensure business users can explore data confidently through self-serve dashboards and curated datasets.
• In addition to data modeling, you’ll implement robust web and app analytics tracking using JavaScript and tools like Google Tag Manager, GA4, Segment, and Adobe Analytics.
• Your work will ensure accurate and consistent event data collection to power downstream reporting, personalization, and marketing attribution. This role requires strong expertise in analytics engineering practices, SQL (BigQuery preferred), dbt, JavaScript for analytics implementation, and BI tools such as Looker or Power BI.

Senior Analytics Engineer

Product Specialist

• Take ownership of the full product lifecycle for one or more web platforms, including marketing sites, content hubs, and fan-facing event experiences.
• Define and maintain a product vision and roadmap that aligns with business objectives and seasonal content or event schedules.
• Prioritize features and improvements using data, fan feedback, and business impact.
• Partner with content and editorial teams to streamline content creation, publishing, and personalization through CMS-driven workflows.
• Ensure all experiences are intuitive, accessible, and optimized across devices, while balancing innovation with platform stability and performance.
• Write clear product requirements, user stories, and acceptance criteria.
• Collaborate with Engineering and Design on delivery, testing prototypes, and gathering user feedback.
• Manage backlogs, coordinate releases, and track dependencies across teams to deliver features on time and at quality.
• Define success metrics, track performance, and use analytics and experimentation to continuously improve engagement, conversion, and retention.
• Serve as the main point of contact for internal stakeholders, communicate progress, clarify priorities, and align teams around shared objectives.