Sr Architect
Syneos Health® is a leading fully-integrated life sciences services organization built to accelerate customer success. We partner with innovators at every point across the drug development and commercialization continuum, helping them navigate complexity, anticipate change and accelerate progress.
Every day we perform better because of how we work together, as one team, each the best at what we do. We bring together talented experts across a broad spectrum of business critical corporate functions. Every role plays an essential part in enabling our customers to achieve their goals. Our teams are agile, collaborative, and committed to delivering—for each other, for our customers, and ultimately for the people who rely on the services we support.
Discover what your 25,000 future colleagues already know:
Why Syneos Health
• We are passionate about developing our people, through career development and progression; supportive and engaged line management; technical and therapeutic area training; peer recognition and total rewards program.
• We are committed to building an inclusive culture – where you can authentically be yourself. Central to this is our purpose – Driven to Deliver – which captures the passion of our colleagues to show up each day and shape solutions that have the ability to dramatically impact someone’s life.
• We are continuously building the company we all want to work for and our customers want to work with. Why? Because we know that when we bring together smart colleagues from across the world, we can shape the future of healthcare, driving impact for customers and defining the pace of patient progress.
Job Responsibilities
.JOB RESPONSIBILITIES
AI-enabled solution architecture
· Lead end-to-end architecture for assigned AI-enabled and automation initiatives, spanning applications, data and knowledge, models, orchestration, agents, APIs, integration, cloud services, identity, security, observability, and operations.
· Translate business outcomes, functional needs, non-functional requirements, and regulatory obligations into architecture options, technical designs, and implementation guidance.
· Design for production scalability, resilience, performance, interoperability, maintainability, portability, and reuse, including workload sizing, capacity assumptions, failure modes, service limits, and operational dependencies.
· Define and develop practical patterns for generative AI, machine learning, intelligent workflows, agentic automation, retrieval and context, tool integration, human oversight, and exception handling when relevant to the project.
AI scalability, economics & operational readiness
· Make cost a first-class architecture concern by assessing consumption drivers such as model usage, tokens, compute, storage, data movement, licensing, vendor services, and support effort.
· Create cost and capacity scenarios for prototype, launch, and scaled adoption; identify material cost-performance-quality trade-offs; and recommend fit-for-purpose models, hosting patterns, caching, routing, batching, quotas, and scaling controls.
· Embed telemetry, usage metering, cost attribution, budgets or thresholds, performance monitoring, quality evaluation, and operational alerts into the solution design so teams can make evidence-based scale, optimize, or stop decisions.
· Partner with platform, FinOps, operations, and product stakeholders to establish ownership, service expectations, support models, lifecycle controls, and continuous optimization practices before production adoption.
· Evaluate build, buy, reuse, and retire options using business value, total cost, architecture fit, delivery risk, security, compliance, vendor dependency, and long-term operability.
Automation advancement across core technology
· Identify and shape high-value automation opportunities across Enterprise Architecture and Enterprise Technology & Platforms, to streamline, simplify and elevate intelligence related to complex technical service delivery processes.
· Advance automation-as-a-capability by designing reusable workflows, APIs, events, templates, policy-as-code, architecture-as-code, and paved-road patterns that reduce manual effort and improve consistency.
· Lead focused proofs of value and production pilots with clear hypotheses, success measures, guardrails, and exit criteria; convert validated learning into reusable patterns, backlog recommendations, standards, or scaled implementation plans.
· Promote human-centered automation that preserves appropriate review, accountability, transparency, and fallback paths for material decisions and regulated processes.
Architecture governance, security & responsible AI
· Apply enterprise architecture principles, approved technology standards, security and privacy requirements, data governance, responsible AI expectations, and regulatory controls throughout the delivery lifecycle.
· Apply project guardrails for data handling, model and provider use, identity and access, content safety, prompt and configuration management, intellectual property, auditability, evaluation, monitoring, human oversight, and incident response.
· Facilitate architecture reviews, document decisions and exceptions, surface material risks and dependencies early, and drive accountable remediation with delivery owners.
· Assess emerging technologies and vendors through structured experiments and architecture reviews, separating credible enterprise value from unsupported novelty.
Delivery leadership, collaboration & knowledge transfer
· Provide architectural leadership at the project level throughout discovery, planning, design, backlog refinement, implementation, testing, release, and transition to operations; remain engaged to validate that delivered solutions conform to approved architecture.
· Collaborate closely with solution architects, engineers, data teams, platform teams, security, operations, product managers, program leaders, and business stakeholders to resolve cross-domain decisions and delivery constraints.
· Communicate complex technology choices in clear business terms, including value, cost, risk, quality, scalability, and delivery implications; present recommendations to architecture and project governance forums.
· Collaborate across teams to develop reusable reference architectures, patterns, templates, decision guidance, and implementation assets; contribute lessons learned to the Enterprise Architecture community of practice.
· Mentor architects and engineers through project work, design reviews, pairing, and knowledge sharing, while retaining the role’s individual-contributor focus.
QUALIFICATION REQUIREMENTS
· Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related field; master’s degree preferred. Equivalent experience, skills, and education will be considered.
· Minimum of 5 years of experience in software, solution, enterprise, cloud, platform, data, or AI architecture, with demonstrated delivery of large-scale or business-critical systems.
· Experience designing and guiding complex solutions across cloud, applications, data, APIs, integrations, security, and operational environments.
· Working knowledge of modern AI architecture, including generative AI, model and provider selection, retrieval and context patterns, agents and tool use, MLOps or LLMOps, evaluation, observability, and responsible AI controls.
· Demonstrated ability to design for scalability and reliability and to analyze technology economics, consumption-based services, capacity, total cost, and cost-performance-quality trade-offs.
· Experience advancing automation through APIs, workflow platforms, event-driven integration, infrastructure or policy as code, platform engineering, DevSecOps, or similar methods.
· Strong problem-solving, facilitation, communication, and documentation skills, with the ability to influence across functions and explain technical decisions to both engineering and business audiences.
· Ability to work independently, lead project architecture through ambiguity, manage competing constraints, and drive decisions and outcomes without relying on direct authority.
Preferred qualifications
· Experience in a regulated industry, healthcare, life sciences, or clinical and commercial technology environments.
· Experience with enterprise architecture methods, product operating models, Agile delivery, architecture decision records, technology governance, and portfolio or lifecycle management.
· Relevant architecture, cloud, data, AI, security, automation, Agile, IT service management, or FinOps certifications.
Get to know Syneos Health
Over the past 5 years, we have worked with 94% of all Novel FDA Approved Drugs, 95% of EMA Authorized Products and over 200 Studies across 73,000 Sites and 675,000+ Trial patients.
No matter what your role is, you’ll take the initiative and challenge the status quo with us in a highly competitive and ever-changing environment. Learn more about Syneos Health.
Additional Information
Tasks, duties, and responsibilities as listed in this job description are not exhaustive. The Company, at its sole discretion and with no prior notice, may assign other tasks, duties, and job responsibilities. Equivalent experience, skills, and/or education will also be considered so qualifications of incumbents may differ from those listed in the Job Description. The Company, at its sole discretion, will determine what constitutes as equivalent to the qualifications described above. Further, nothing contained herein should be construed to create an employment contract. Occasionally, required skills/experiences for jobs are expressed in brief terms. Any language contained herein is intended to fully comply with all obligations imposed by the legislation of each country in which it operates, including the implementation of the EU Equality Directive, in relation to the recruitment and employment of its employees. The Company is committed to compliance with the Americans with Disabilities Act, including the provision of reasonable accommodations, when appropriate, to assist employees or applicants to perform the essential functions of the job.