AI Architect

QuartzBio Overview:

QuartzBio (www.quartz.bio ) is a Software-as-a-Service (SaaS) solutions provider to the life sciences industry. We deliver innovative, data enabling technologies (i.e., software) that provide biotech/pharma (R&D) teams with enterprise-level access to sample/biomarker data management solutions & analytics, information, insight & reporting capabilities.

Our end-to-end (from sample collection to biomarker data) suite of solutions are focused on providing sponsors information (data with context) – we do this by connecting biospecimen, assay as well as clinical data sources in a secure and scalable cloud-based infrastructure, enabling seamless, automated data management workflows, key insight development, improved collaboration, and the ability to make faster, more informed decisions.

Position Summary:

As AI Architect, you will play a pivotal role in defining and delivering the architecture, strategy, and execution of advanced GenAI systems that power our core products and enable intelligent exploration of biomarker data. You will lead the technical direction of the AI engineering function, ensuring cross-team alignment and driving long-term roadmap planning.

In this leadership role, you will architect complex, scalable GenAI pipelines, guide technical design across squads, and influence executive-level decision-making around AI strategy, tooling, and infrastructure. You will also champion best practices in AI-first development, mentor engineering talent, and drive the adoption of emerging AI technologies to ensure our systems remain at the forefront of innovation.

Key Responsibilities:

• Architect and lead the development of next-generation RAG systems using vector databases, semantic embeddings, and cloud-native services.
• Design and implement scalable, production-ready GenAI pipelines and LLM-based services to power intelligent, conversational exploration of biomarker data.
• Collaborate across Product, Engineering, and Design to align AI architecture with roadmap priorities and user needs.
• Own key architectural decisions around model orchestration, latency optimization, prompt design, and scalability
• Strategic technical advisor to leadership and help prioritize AI investments with long-term impact.
• Provide technical leadership across squads, driving design reviews, AI solution quality standards, and architectural consistency.
• Lead internal initiatives to adopt and evaluate emerging AI/LLM frameworks, orchestration platforms, and foundation models.
• Define and refine LLM evaluation frameworks, feedback pipelines, and end-user quality metrics.
• Champion best practices for AI-first development, observability, versioning, and experimentation
• Serve as a mentor and multiplier, developing talent across the AI engineering organization.
• Drive strategic AI initiatives aligned with business goals.
• Subject matter expert in AI and machine learning technologies.
• Draft and maintain internal documentation for relevant AI systems and processes; communicate within and across teams.
• Debug and troubleshoot complex AI system issues and provide timely solutions.
• Mentor and develop AI engineers; help scale the AI organization through strategic hiring, training, and leadership.
• Communicate effectively with team members and stakeholders.
• Collaborate with cross-functional teams to define AI project requirements and timelines.
• Continuously improving technical skills and staying up to date with emerging AI technologies and shifting priorities
• Other duties as assigned.

Qualifications:

• Bachelor’s degree related field and a minimum of 12 years of relevant work experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions.
• 10+ years of engineering experience, including 5+ years shipping production ML/AI systems, with a focus on LLMs or GenAI
• 6-8 years of experience working in a customer-facing role and leading projects.
• Proven experience driving architecture and strategy for complex AI systems at scale
• Deep expertise in Python, cloud platforms (especially AWS), and modern AI/ML infrastructure
• Advanced proficiency with semantic search, vector databases, and retrieval-augmented generation (RAG) architectures
• Experience working with LLM tooling such as Lang Chain, Llama Index, AWS Bedrock, OpenAI, or similar
• Familiarity with evaluation pipelines, human-in-the-loop feedback systems, and performance optimization
• Strong systems thinking and algorithmic fundamentals (DSA)
• Excellent communication skills, with a track record of aligning stakeholders and driving strategic initiatives.
• Comfortable in AI-native environments using tools like GitHub Copilot, Cursor, or related development assistants.
• Strong ability to identify and present information or data that will have a strong effect on others.
• Strong ability to partner with customers.
• Strong ability to review and understand end-to-end work processes.
• Skilled at collaborating with customers to understand their requirements and expectations by asking questions and listening.
• Excellent problem-solving and analytical skills.

Leadership expectations:

• Follows Company's Principle and code of ethics on a day-to-day basis.
• Shows appreciation for individual talents, differences, and abilities of fellow team members.
• Listens and responds with appropriate actions.
• Leads change initiatives and continuous process improvements.