Senior Architect, Intelligent Solutions Engineering

Description de l'emploi

We are seeking a Senior Architect, Intelligent Solutions who thrives in a hybrid role that blends technical leadership with hands-on delivery. In this role, you will serve as the technical lead for contractor engineering teams, own delivery outcomes for your function within cross-functional initiatives, and remain deeply engaged in the work itself, contributing to architecture, solution design, and complex problem-solving.

You will oversee a portfolio of clinical solutions spanning both modern, AI-powered capabilities, including generative AI, LLMs, and intelligent automation, and production business applications. Bringing deep, practical experience applying AI across the full development lifecycle, you will leverage AI-powered development assistants to accelerate ideation, design, coding, testing, and troubleshooting.

You will expand your leadership impact by partnering closely with stakeholders, data scientists, and engineers while continuing to work hands-on with systems that deliver measurable improvements in clinical development workflows and decision-making.

Key Responsibilities

• Architect, design, and deliver AWS cloud-native solutions across AI/ML capabilities and enterprise business applications.
• Lead the implementation of Generative AI solutions, including retrieval-augmented generation (RAG), agentic workflows, and LLM-integrated systems.
• Drive adoption of AI-augmented development practices, including design acceleration, code generation and review, test automation, and debugging.
• Serve as the primary technical authority for assigned capabilities, making architectural decisions across APIs, data platforms, frontend, infrastructure, and AI tooling.
• Lead technical delivery across onshore and offshore contractor teams, ensuring predictable planning, execution quality, and delivery outcomes.
• Mentor and coach engineers through hands-on guidance, pair programming, code reviews, and knowledge sharing.
• Partner with data science, business, quality, and regulatory stakeholders to align architecture and delivery with program milestones and compliance needs.
• Prototype and validate new capabilities, particularly Generative AI features, to reduce risk before broader team investment.
• Define and execute a technical roadmap aligned with business priorities and R&D Information Systems strategy.
• Oversee production reliability, operational support, and continuous improvement across DevOps and engineering practices.

Basic Qualifications

• BA/BS with at least 8 years of experience, MA/MS/MBA with at least 6 years of experience, OR PhD with at least 2 years of experience.
• Strong experience in architecture and system design for scalable, cloud-native applications.
• Demonstrated ability to provide cross-functional technical leadership and own delivery outcomes.
• Practical experience using AI-powered development tools to accelerate design, implementation, and troubleshooting.
• Working knowledge of Generative AI concepts, including LLMs, prompt and context engineering, and agent-based systems.
• Experience with AI orchestration frameworks, such as LangChain, or the ability to ramp up quickly.
• Strong Python development skills, including REST APIs (FastAPI), asynchronous programming, and testing.
• Experience with modern frontend frameworks, such as React, including component architecture and state management.
• Experience with relational and NoSQL databases, including schema design, query development, and performance tuning.
• Strong AWS experience, including ECS or EKS, Lambda, S3, DynamoDB, RDS, and SQS.
• Experience with infrastructure as code (Terraform), CI/CD (GitHub Actions), containers (Docker and Kubernetes), and cloud security fundamentals.
• Proven experience leading contractor or vendor engineering teams while remaining hands-on.
• Ability to communicate technical decisions clearly to both technical and non-technical stakeholders.

Preferred Qualifications

• Experience in pharmaceutical or healthcare environments, particularly clinical development.
• Familiarity with GxP, 21 CFR Part 11, and related regulatory frameworks.
• Experience deploying and operating AI or ML solutions in production, including model or LLM evaluation, and monitoring.