锦鲤求职岗位描述
Position Overview
As the head of AI engineering and product delivery, you will lead the technical architecture, engineering execution, and product strategy for AI-powered clinical trial solutions. You are both a technical leader and a product visionary—responsible for building high-availability, scalable, and compliant AI systems, while also translating cutting-edge AI capabilities into tangible product value that addresses real customer pain points, and driving commercial success through cross-functional leadership.
Key Responsibilities
Product Strategy & Roadmap
Own the overall product strategy and roadmap for AI-powered clinical trial solutions, defining product positioning, core features, and differentiation based on market insights, customer needs, and competitive landscape.
Establish product prioritization frameworks, balancing short-term delivery with long-term technology investments to ensure continuous alignment with business objectives.
Engineering Architecture & Technical Leadership
Lead the overall technical architecture design of AI products, building high-performance, secure, and compliant RAG pipelines, Agent workflows, and microservices architectures.
Oversee technology stack selection, system performance optimization, and technical debt management, ensuring scalability, stability, and maintainability of the system.
Lead the full lifecycle engineering of LLM applications (e.g., intelligent document processing, automated query generation, monitoring assistants, protocol writing assistance) from proof-of-concept to large-scale production deployment.
Team Development & Management
Build and lead cross-functional engineering and product teams, including backend, frontend, DevOps, product managers, and UI/UX designers.
Establish efficient product development processes (e.g., Agile/Scrum), driving continuous improvement in quality, efficiency, and innovation.
Own team recruitment, development, performance management, and career growth.
Compliance, Quality & Safety
Lead the design and implementation of AI safety guardrails, evaluation frameworks, and observability solutions to ensure AI outputs meet the stringent accuracy, traceability, and compliance requirements of the life sciences industry (e.g., GCP, 21 CFR Part 11, FDA guidance).
Drive the adoption of CI/CD and MLOps/LLMOps best practices to ensure reliable system delivery.
Customer & Commercial Engagement
Partner closely with customer success, business development, and clinical operations teams, participating in key client demos and requirements discussions to translate technical capabilities into customer-perceived value.
Monitor industry trends and competitive intelligence, continuously refining product positioning and competitiveness.
Qualifications
Education
Master's degree or above in Computer Science, Software Engineering, Information Technology, or a related field (exceptional candidates with a Bachelor's degree may be considered).
Experience
8+ years of experience in software engineering or AI product development, with at least 3+ years in engineering or product team management roles.
Proven experience leading AI-driven products from 0 to 1, particularly in life sciences, clinical research, or healthcare, is highly preferred.
Technical Skills
Expert-level proficiency in Python, Java, or TypeScript, with deep understanding of cloud-native architectures (AWS/Azure/GCP), microservices, and RESTful API design.
Deep expertise in LLM application development frameworks (e.g., LangChain, LlamaIndex), vector databases, and Agent architecture design.
Familiarity with MLOps/LLMOps toolchains and methodologies, with hands-on experience in architecting and operating production-grade AI systems.
Knowledge of clinical data systems (e.g., EDC, CTMS, ePRO) and 21 CFR Part 11 compliance requirements is a plus.
Core Competencies
Strong combination of technical depth and product mindset, with the ability to bridge technology and business needs across domains.
Exceptional cross-functional leadership and communication skills, capable of building consensus and driving execution across engineering, product, clinical, and commercial teams.
Strong customer orientation and results-driven mindset, with genuine passion for applying AI to solve real-world challenges in healthcare and life sciences.