Research client markets, competitors, and technology trends; analyze data and business processes; and support the development of strategies, roadmaps, and business cases. Help gather client input, create deliverables and prototypes with design and engineering teams, track project progress and outcomes, and contribute to transformation work and thought leadership.
Design, build, and deploy full-stack applications using Python, FastAPI, React, and TypeScript, including production LLM applications with retrieval, search, and document-processing capabilities. Maintain applications on Azure, monitor and improve LLM quality, and work directly with clients to turn business needs into practical technical solutions.
Conduct and synthesize research, identify experience opportunities, and design and prototype conversational, adaptive, and generative AI interfaces. Collaborate with engineers, clients, and senior designers to develop scalable design systems, test interaction patterns, and communicate design decisions clearly.
Conduct end-to-end privacy reviews for AI, machine learning, and LLM systems to identify risks and recommend safeguards. Partner with cross-functional teams to ensure privacy controls are integrated throughout the product lifecycle.
Design, build, evaluate, and maintain AI agent capabilities, integrations, and reusable application templates, while developing developer-facing tools with React and TypeScript. Improve engineering workflows and quality gates, integrate AI capabilities with infrastructure and CI/CD, and document and monitor platform behavior to guide ongoing improvements.
Design, build, and operate secure, reliable cloud infrastructure and platform capabilities, including networking, CI/CD, observability, secrets management, disaster recovery, and infrastructure automation. Partner with AI engineering teams to support agent-based workflows and ephemeral development environments while improving platform stability, security, and developer experience.
Design, build, and maintain scalable data pipelines and ELT transformations using SQL and dbt, while managing infrastructure with Terraform. Develop and support web applications using Node.js, TypeScript, GraphQL, and React; collaborate across teams, improve production reliability, and participate in code reviews and the on-call rotation.
Design and develop backend applications using Java and microservices with Quarkus while maintaining frontend solutions in Angular. Implement event-driven solutions on AWS and contribute to architecture, observability, and engineering productivity.
Design, develop, and maintain backend applications and services using Java, Spring Boot, and microservices architecture. Collaborate with cross-functional teams to analyze requirements, implement technical solutions, and ensure high performance and scalability.
Develop software and automated unit tests, completing assigned tasks within agreed timeframes while collaborating with project teams, managers, and end users. Participate in technical discussions and improve existing systems through refactoring and optimization for performance, maintainability, and scalability.
The QA Engineer will review business requirements to create and execute detailed test scenarios, including functional, integration, and regression testing. They will also document defects, perform data validation, and coordinate with technical teams to ensure system stability and quality.
Design and implement end-to-end document intelligence pipelines on AWS while developing and optimizing machine learning models for document classification and extraction. You will own features from research through production deployment and establish quality metrics for extraction accuracy.
Translate business requirements into ControllerView configurations and support the design, implementation, and enhancement of AxiomSL regulatory reporting solutions. Analyze and improve data flows and reporting processes, validate data quality, support report generation and exception management, and document business processes while collaborating with business, risk, compliance, and technology stakeholders.
The Solutions Consultant will redesign and optimize HubSpot pipeline structures, automation workflows, and data governance practices to improve sales efficiency. They will also partner with sales leadership to develop custom reporting dashboards and provide enablement support to ensure platform adoption.
Collaborate with stakeholders to translate complex business processes into structured, executable instructions for AI agents. Design, implement, and maintain reusable Claude Code skills while providing technical leadership and defining platform-level standards.
