Jobs at CAS

People-leadership role managing and growing a team of data scientists and AI engineers building retrieval, extraction, and reasoning systems for scientific discovery products. Focus on hiring, coaching, performance management, team health, cross-team initiatives, and communicating work to stakeholders. Maintain technical fluency in LLMs, RAG, agentic workflows, and evaluation to mentor teams, while partnering with technical leads and product owners.

Manages academic customer accounts by onboarding users, driving product adoption, resolving issues, identifying expansion opportunities, and maintaining executive relationships. Conducts consultative sales, presentations, needs assessments, and territory development while tracking activity in CRM systems. Monitors usage and customer risks, supports retention and renewals, attends industry events, and uses AI tools to analyze customer, contract, and market data.

Manage and grow assigned North American accounts while generating new business for CAS scientific information and IP services. Responsibilities include consultative solution selling, prospecting, pipeline development, account retention, cross-selling, contract negotiations, RFP responses, product demonstrations, and executive-level customer engagement. The role collaborates with internal scientific, IP services, product, marketing, and delivery teams to create customized solutions and maintain accurate CRM forecasts.

Provides pre- and post-sale technical consulting, product demonstrations, training, and customized instructional materials for scientific information solutions. Collaborates with sales to match customer needs to products, identify expansion opportunities, gather feedback, and communicate product value. Requires chemistry knowledge, strong presentation skills, scientific information expertise, multilingual fluency, rapid learning ability, and willingness to travel.

Design, build, evaluate, and productionize agentic AI, LLM, RAG, and predictive ML systems for scientific information products. Develop training and inference pipelines, fine-tune models, establish trustworthy-AI evaluation and safeguards, and operate AI capabilities at scale. Set engineering standards, lead technical initiatives, mentor scientists and engineers, influence product and executive decisions, and communicate results through presentations, publications, and client engagements.

Design, build, automate, and support cloud infrastructure and CI/CD for production systems. Run and optimize EKS/Kubernetes at scale, implement IaC (Terraform), observability, security best practices, disaster recovery, and cost optimization. Collaborate with engineering teams, participate in on-call incident response, and produce architecture documentation and operational runbooks.