高级人工智能工程师/AI 负责人
Senior AI Engineer/AI Lead
当我们的价值观一致时,我们能够实现无限可能。
在Parexel,我们都有相同的目标——改善全球健康。从临床试验到监管、咨询和市场准入,我们提供的每项临床开发解决方案都建立在一个特别的基础之上——对所做工作的深刻信念。
无论我们在Parexel做什么,每个人都在推动一种最终将惠及患者的疗法的发展。我们认真对待工作,以同理心去做,并致力于带来改变。
我们正在寻找一位高级AI工程师/AI负责人加入我们的团队。作为高级AI工程师/AI负责人,你将推动设计和实现一个尖端的多智能体AI平台,改变不良事件数据在药物警戒中的处理和管理方式。这个职位在推进临床研究自动化、确保监管合规性以及建立药物安全运营的新标准方面起着关键作用。你将与跨职能团队合作,包括领域专家、质量保证和监管专家,遵循行业标准流程,并从架构到验证和部署参与系统开发。职责包括设计和实现先进的AI智能体编排,定义评估框架,构建与企业系统的安全集成,并确保GxP合规性,有大量机会影响技术方向,推动AI治理的创新,并扩展你在受监管AI系统方面的专业知识。
你将加入一个快节奏、注重成长的环境,通过推进药物警戒自动化、提高数据准确性和安全监督,以及确立Parexel在AI驱动临床研究领域的领导地位来产生有意义的影响。拥有多样化的团队和持续的学习机会,高级AI工程师/AI负责人可以探索新兴技术,指导初级工程师,并拓展在AI架构、监管合规和医疗保健创新方面的技能。
主要职责
- 使用AWS Bedrock、AgentCore、Strands SDK和/或LangGraph设计和实现多智能体架构,以Anthropic Claude作为基础模型层
- 定义智能体拓扑结构,包括主管编排、智能体间通信、状态管理、升级路由和全面的审计追踪基础设施
- 负责提示工程
查看英文原文
When our values align, there's no limit to what we can achieve.
At Parexel, we all share the same goal - to improve the world's health. From clinical trials to regulatory, consulting, and market access, every clinical development solution we provide is underpinned by something special - a deep conviction in what we do.
Each of us, no matter what we do at Parexel, contributes to the development of a therapy that ultimately will benefit a patient. We take our work personally, we do it with empathy and we're committed to making a difference.
We are seeking a Senior AI Engineer/AI Lead to join our team. As a Senior AI Engineer/AI Lead, you will drive the design and implementation of a cutting-edge, multi-agent AI platform that transforms how adverse event data is processed and managed in pharmacovigilance. This position plays a critical role in advancing clinical research automation, ensuring regulatory compliance, and establishing new standards for safety and efficiency in drug safety operations. You'll collaborate with cross-functional teams including domain experts, quality assurance, and regulatory specialists, following industry-standard processes and contributing to system development from architecture through validation and deployment. Responsibilities include designing and implementing advanced AI agent orchestration, defining evaluation frameworks, architecting secure integrations with enterprise systems, and ensuring GxP compliance, with significant opportunities to influence technical direction, drive innovation in AI governance, and expand your expertise in regulated AI systems.
You'll join a fast-paced, growth-oriented environment focused on making a meaningful impact through advancing pharmacovigilance automation, improving data accuracy and safety oversight, and establishing Parexel as a leader in AI-driven clinical research. With diverse teams and continuous learning opportunities, the Senior AI Engineer/AI Lead can explore emerging technologies, mentor junior engineers, and expand skills across AI architecture, regulatory compliance, and healthcare innovation.
Key Responsibilities
- Design and implement the multi-agent architecture using AWS Bedrock, AgentCore, Strands SDK, and/or LangGraph, with Anthropic Claude as the foundation model layer
- Define the agent topology including supervisor orchestration, inter-agent communication, state management, escalation routing, and comprehensive audit trail infrastructure
- Own the prompt engineering strategy across all pharmacovigilance agents, including system prompts, few-shot examples, and guardrails to ensure accuracy and compliance
- Architect, design, and build Model Context Protocol (MCP) servers to expose enterprise applications, data sources, and services as standardized tools for AI agents
- Build and maintain the evaluation pipeline by designing benchmarks, curating ground-truth datasets with domain experts, and running accuracy and precision measurements
- Architect the quality control layer including cross-model verification, deterministic rule engines for field validation, and auto-escalation logic
- Collaborate with the existing team to migrate current systems to Claude on Bedrock while preserving proven logic and re-engineering prompts and evaluation pipelines
- Define the CI/CD and MLOps strategy including model versioning, prompt version control, deployment of pipelines, monitoring dashboards, and cost tracking
- Own the technical validation strategy aligned to GAMP5 Category 5 requirements, working with QA to produce IQ/OQ/PQ documentation specific to LLM-based systems
- Write and review technical documentation including architecture decision records, algorithm descriptions, and AI model specifications aligned to regulatory frameworks
You'll thrive in this role if you bring:
- Expertise in AI system architecture, prompt engineering, and large language model orchestration
- Experience designing and implementing secure integrations between AI systems and enterprise applications
- The ability to translate complex technical concepts into clear communication for non-technical stakeholders, including regulatory and quality audiences
- A commitment to quality, compliance, and patient safety in regulated environments
- Comfort working with AWS cloud services, Python, and modern AI frameworks and tools
Required Qualifications
- 7+ years of hands-on experience building ML/AI production systems, with at least 2 years working with large language models in application-level contexts
- Deep working knowledge of Anthropic Claude APIs, prompt engineering patterns, and retrieval-augmented generation architectures
- Practical experience with AWS, specifically Bedrock (model invocation, agents, knowledge bases), Lambda, S3, IAM, and CloudTrail
- Experience building multi-agent or multi-step LLM orchestration systems using frameworks such as LangGraph, LangChain, CrewAI, or Strands SDK
- Strong Python and software engineering fundamentals including API design, containerization, infrastructure-as-code, testing, and version control
- Demonstrated ability to design evaluation frameworks for LLM outputs, including accuracy measurement, regression testing, and confidence calibration
- Ability to communicate technical decisions clearly to non-technical stakeholders, including regulatory and quality audiences
- Bachelor's degree in computer science, or a related field, or equivalent professional experience
Preferred Qualifications
- Experience designing and implementing Model Context Protocol (MCP) servers or equivalent tool-serving frameworks
- Familiarity with GxP/regulated software environments, GAMP5 validation, CSV/CSA approaches, or FDA software guidance
- Prior work on document processing pipelines including OCR, PDF extraction, email parsing, or structured data extraction from unstructured clinical text
- Experience with MedDRA or other medical coding dictionaries
- Track record of shipping LLM-based systems in regulated industries such as pharma, healthcare, or fintech
- Exposure to pharmacovigilance, clinical safety, or healthcare data processing
We believe in flexibility, growth, and creating space for people to do their best work. Join us and be part of a team where your contributions help shape the future of clinical research.
If this job doesn't sound like the next step in your career, but perhaps you know of someone who'd be a perfect fit, send them the link to apply!
Originally posted on Himalayas