We are seeking a visionary and hands-on Enterprise Data Integration Architect to join our Integration Architecture team and serve as the dedicated integration representative to partner with the Data & AI organization. This role is pivotal in shaping and executing our enterprise-wide integration strategy for data and AI initiatives, leveraging cutting-edge technologies and cloud-native platforms on AWS and/or Azure.
Responsibilities
Define and drive the integration strategy for data and AI initiatives across the enterprise
Partner with Data & AI leadership to align integration architecture with business goals and data strategies
Evaluate and recommend modern integration technologies and patterns (e.g., event-driven, API-led, streaming, data mesh)
Partner with regional teams in defining and designing integration patterns and architectures
Design scalable, secure, and resilient integration architectures on AWS and/or Azure using services such as Glue, Lambda, Kinesis, S3, Redshift, and others
Requirements
Bachelor’s or Master’s degree in Computer Science
Information Systems, or related field
Nice to have: Azure cloud services
Nice to have: regulated industries (healthcare, finance)
Designing and building production-ready agents, copilots and workflow automations that integrate with our existing systems, data and processes. Embedding with business and product teams to identify, scope and deliver high-value AI solutions from prototype to production, with clear measures of success and defined handover points. Contributing AI-enabled features to member-facing products alongside our Product Engineers, owning your work through deployment and incidents. Evaluating and monitoring AI solutions in production and reporting impact honestly - including cost, error rates and what did not work. Coaching team members while building real solutions so that capability stays with the team after each engagement, and creating reusable playbooks and standards shared across the business. Working daily with the AI Platform Engineer, Tech Leads, Product Leads and AI Ambassadors to use approved models and tooling and contribute reusable components back to the platform. Keeping human oversight and clear accountability at the centre of every solution, working with Information Security and Data Protection throughout.
Responsibilities
Designing and building production-ready agents, copilots and workflow automations that integrate with our existing systems, data and processes.
Embedding with business and product teams to identify, scope and deliver high-value AI solutions from prototype to production, with clear measures of success and defined handover points.
Contributing AI-enabled features to member-facing products alongside our Product Engineers, owning your work through deployment and incidents.
Evaluating and monitoring AI solutions in production and reporting impact honestly - including cost, error rates and what did not work.
Coaching team members while building real solutions so that capability stays with the team after each engagement, and creating reusable playbooks and standards shared across the business.
Lead AI quality and evaluation product strategy, build and experiment with AI agents, and drive customer-facing performance improvements.
Compensation
The typical base salary range for this position is $218,400 - $365,200 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $263,200 - $401,400 annually.
Responsibilities
Set product strategy and roadmap for AI quality and evaluation
Establish shared quality definitions, evaluation requirements, and release criteria
Make investment tradeoffs across customer quality improvements and product features
Lead customer investigations and experiments to validate impact
Build operating approach connecting feedback, evidence, and learning
Lead the development of the OpenTelemetry Python SDK and instrumentation libraries, focusing on AI applications and agent workflows, while contributing to the open-source community and guiding technical direction.
Locations (4)
Germany
United Kingdom
Ireland
Spain
Compensation
In Germany, the compensation range for this role is EUR 113,000 - EUR 141,000.
Responsibilities
Develop improvements to the OpenTelemetry Python SDK and instrumentation libraries
Collaborate with open-source communities and maintainers
Build, enhance, and support generative AI web applications and backend services.
Compensation
Market competitive salary, commensurate with experience and education.
Responsibilities
Build, enhance, and support production generative AI applications and web-based AI solutions.
Develop Python backend services and AI integrations using Azure OpenAI, Azure AI Foundry, and related Azure services.
Implement RAG pipelines, including document processing, chunking, embeddings, search, context preparation, and source citations.
Implement agent workflows using tool/function calling, structured outputs, conversation context, error handling, execution limits, and human review where needed.
Integrate AI applications with APIs, enterprise data sources, databases, cloud services, and MCP-based tools.
Requirements
Bachelor's degree in computer science, engineering, or a related field
Independently translate business and system requirements into pragmatic designs, modular code, rapid AI proofs of concept (PoCs), minimum viable products (MVPs), and production-ready applications.
Build AI-powered applications and backend services using hosted foundation-model APIs, SDKs, enterprise data, and reusable services; evaluate ideas quickly and recommend whether they should progress, pivot, or stop.
Build end-to-end Retrieval-Augmented Generation (RAG) solutions covering ingestion, chunking, embeddings, vector or hybrid retrieval, reranking, grounding, citations, and permission-aware responses.
Build and integrate Model Context Protocol (MCP) clients and servers that expose enterprise tools, prompts, resources, data, and services through standardized, governed, and auditable interfaces.
Develop agentic workflows using tool calling, orchestration, state and memory patterns, structured outputs, guardrails, confidence controls, output validation, and human-in-the-loop approvals.
Requirements
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent practical experience.
Nice to have: Experience in payments
Nice to have: high-volume transaction processing
Nice to have: highly available and regulated technology environments
Senior Software Engineer in the Builder Experience team, responsible for building and maintaining the shared AI foundation that powers internal AI tools and services.
Responsibilities
Build the paved path: agent harness, orchestration, model access layer, MCP servers, CI/CD, observability, cost tracking
Set standards for AI-generated code and high-risk paths
Run workshops, office hours, and pair with engineering and product teams
Mentor BX students and guide their work
Track adoption, delivery speed, quality and cost metrics
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