Senior Technical Architect

The Sr. Technical Architect is responsible for supporting Fortrea's technology vision, solution architecture strategy, and engineering architecture standards across the company's digital products, platforms, and technology portfolio.

This role provides senior technical leadership by supporting cloud-native architecture patterns, AI-enabled architecture, engineering standards, integration strategies, platform engineering capabilities, reusable technology frameworks, and architecture governance that enable secure, scalable, resilient, high-performing, and AI-ready software solutions.

As one of Fortrea's senior technical leaders, the Sr. Technical Architect partners closely with Product Management, Product Engineering, Platform Engineering, Data & AI, Security, Infrastructure, and Enterprise Architecture to ensure technology investments align with business priorities while accelerating innovation and long-term platform evolution.

The Sr. Technical Architect serves as a trusted technical advisor by driving modernization initiatives, enabling AI-powered software development, providing technical guidance to project teams and less-experienced colleagues, supporting engineering standards, and promoting engineering excellence across the Global Digital Foundry.

Hybrid Role in Warsaw.

Summary of Responsibilities:

• Support long-term solution architecture strategy, technology roadmaps, architecture principles, and technical standards across Fortrea's digital products and platforms.
• Support enterprise architecture standards, reusable design patterns, reference architectures, architecture decision records (ADRs), engineering guardrails, and governance processes that promote consistency, scalability, maintainability, and reuse.
• Support cloud-native architecture patterns utilizing Microsoft Azure, Kubernetes, containers, serverless computing, API-first design, event-driven architectures, distributed systems, and modern software engineering practices.
• Support solution architecture for digital products, SaaS platforms, APIs, integrations, mobile applications, cloud services, and shared engineering platforms.
• Define enterprise AI architecture patterns supporting Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, Model Context Protocol (MCP), vector databases, prompt orchestration, intelligent automation, and Responsible AI.
• Partner with Data & AI teams to define reusable AI platform capabilities, enterprise AI governance, model integration strategies, and AI engineering standards.
• Drive architecture modernization initiatives including cloud migration, platform engineering, application modernization, technical debt reduction, API modernization, microservices adoption, and platform consolidation.
• Design reusable engineering platforms, shared services, Internal Developer Platforms (IDPs), developer enablement capabilities, and engineering accelerators that improve developer productivity.
• Define enterprise integration strategies including API Management, event streaming, messaging, asynchronous architectures, interoperability frameworks, FHIR/HL7 integration (where applicable), and secure service communication.
• Establish enterprise data architecture principles supporting Microsoft Fabric, cloud data platforms, analytics, data products, streaming architectures, governance, and enterprise data interoperability.
• Lead architecture reviews, technical assessments, proof-of-concepts, design workshops, technology evaluations, and solution design activities.
• Partner with Product Engineering leadership to ensure architecture aligns with customer needs, business priorities, product roadmaps, and engineering execution.
• Define architecture standards for security, Zero Trust, identity management, API security, secrets management, software supply chain security, privacy, compliance, resilience, observability, and operational excellence.
• Provide technical guidance to project teams and less-experienced colleagues by promoting software craftsmanship, engineering excellence, AI-assisted development, and architecture best practices.
• Build and lead Technical Architecture Communities of Practice that promote innovation, collaboration, reusable solutions, mentoring, technical standards, and continuous learning.
• Collaborate with Enterprise Architecture to align solution architecture with enterprise strategy, business capabilities, technology investments, and long-term transformation initiatives.
• Continuously evaluate emerging technologies including AI platforms, cloud services, engineering tools, developer productivity platforms, and software architecture trends that improve engineering effectiveness and customer outcomes.
• Establish architecture health metrics including technical debt reduction, architecture compliance, platform adoption, solution reuse, engineering productivity, operational reliability, and modernization progress.
• Identify architectural risks, technology constraints, operational dependencies, scalability challenges, and recommend mitigation strategies.
• Champion engineering excellence through reusable architecture, documentation standards, engineering best practices, software craftsmanship, and technical governance.
• Participate in technology strategy, architecture councils, engineering planning, executive technology discussions, and strategic investment decisions.
• Perform other duties as assigned.

Qualifications (Minimum Required):

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, Engineering, or related discipline. Equivalent experience will be considered.
• Deep expertise in enterprise software architecture, cloud-native application design, distributed systems, APIs, microservices, integration architecture, and modern software engineering practices.
• Strong knowledge of Microsoft Azure, Kubernetes, cloud-native platforms, containers, Infrastructure as Code, Platform Engineering, and modern application architecture.
• Strong understanding of Domain-Driven Design (DDD), Event-Driven Architecture, CQRS, Event Sourcing, Clean Architecture, Hexagonal Architecture, API-first design, and enterprise integration strategies.
• Strong understanding of AI platform architecture, intelligent automation, cloud-native AI services, and modern AI engineering principles.
• Expertise designing scalable, secure, resilient, observable, and highly available enterprise technology platforms.
• Strong knowledge of enterprise data architecture, cloud data services, data governance, integration platforms, and analytics ecosystems.
• Deep understanding of Zero Trust, identity management, secure software development lifecycle, privacy, software supply chain security, and regulatory compliance.
• Excellent communication, presentation, technical leadership, executive influence, and stakeholder management skills.
• Demonstrated ability to influence engineering organizations and executive leaders without direct management authority.

Experience (Minimum Required): 

• 10+ years of progressive experience in Software Engineering, Solution Architecture, Technical Architecture, Platform Engineering, or related engineering disciplines.
• 5+ years designing enterprise-scale SaaS platforms, digital products, APIs, cloud-native applications, distributed systems, and enterprise integrations.
• Demonstrated success supporting architecture strategies, technology roadmaps, engineering standards, and reusable architectural frameworks.
• Experience designing cloud-native platforms using Microsoft Azure, Kubernetes, Infrastructure as Code, containers, APIs, event-driven architectures, and microservices.
• Experience designing AI-enabled enterprise solutions using Azure OpenAI, OpenAI APIs, AI agents, Retrieval-Augmented Generation (RAG), intelligent automation, or machine learning services.
• Experience defining enterprise AI architecture, Responsible AI standards, AI governance, model integration strategies, and secure AI software development.
• Proven experience establishing API strategies, integration architectures, interoperability standards, messaging platforms, and enterprise integration patterns.
• Experience leading cloud transformation, application modernization, platform engineering, technical debt reduction, and enterprise modernization initiatives.
• Experience partnering with Product Management, Product Engineering, Platform Engineering, Data & AI, Security, Infrastructure, Enterprise Architecture, and executive leadership.
• Experience conducting architecture reviews, technical governance, design reviews, proof-of-concepts, technical assessments, and technology evaluations.
• Demonstrated success balancing customer needs, business priorities, operational requirements, technical constraints, and long-term technology strategy.

Preferred Qualifications Include:

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, Engineering, or related discipline.
• Experience within healthcare, life sciences, clinical research, digital health, medical devices, or other highly regulated industries.
• Experience designing enterprise AI platforms using Azure OpenAI, OpenAI APIs, Anthropic Claude, Google Vertex AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, Model Context Protocol (MCP), vector databases, and intelligent automation.
• Experience implementing Responsible AI architecture, AI governance, model evaluation, prompt engineering, AI security, and enterprise AI platforms.
• Expertise with Microsoft Azure, Azure Kubernetes Service (AKS), Azure API Management, Microsoft Fabric, Azure Landing Zones, Azure DevOps, GitHub Enterprise, GitHub Actions, Terraform, Bicep, Kubernetes, Docker, Helm, and Infrastructure as Code.
• Experience implementing Internal Developer Platforms (IDPs), Platform Engineering, reusable engineering services, developer portals, and developer enablement capabilities.
• Experience with modern architecture practices including Domain-Driven Design (DDD), Event Sourcing, CQRS, Clean Architecture, Hexagonal Architecture, GraphQL, event-driven systems, and API-first architecture.
• Experience implementing enterprise observability using OpenTelemetry, Azure Monitor, Datadog, Dynatrace, Grafana, Prometheus, Elastic, or similar platforms.
• Familiarity with AI-assisted software engineering using GitHub Copilot Enterprise, GitHub Models, Cursor, Claude Code, Windsurf, ChatGPT Enterprise, or equivalent developer productivity platforms.
• Relevant certifications including TOGAF, Microsoft Azure Solutions Architect Expert, AWS Solutions Architect Professional, Google Professional Cloud Architect, Kubernetes (CKA/CKAD), or equivalent architecture certifications.
• Demonstrated success supporting architecture modernization, contributing to technology decisions, providing technical guidance to less-experienced colleagues, and supporting engineering standards across large-scale engineering organizations
• undefinedPhysical Demands / Work Environment:Office/Home-Based:Work Environment:Work is performed in an office environment with exposure to electrical office equipment.Occasional drives to site locations with occasional travel both domestic and international. Physical Requirements:Frequently stationary for 6-8 hours per day.Repetitive hand movement of both hands with the ability to make fast, simple, repeated movements of the fingers, hands, and wrists.Occasional crouching, stooping, with frequent bending and twisting of upper body and neck.Ability to access and use a variety of computer software developed both in-house and off-the-shelf.Light to moderate lifting and carrying, or moving of objects, including luggage and laptop computer with a maximum lift of 15-20 lbs.Regular and consistent attendance.Varied hours may be required. 

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