Director, AI Small Molecule Drug Design

SystImmune is a leading and well‑funded clinical‑stage biopharmaceutical company located in Redmond, WA and Princeton, NJ. It specializes in developing innovative cancer treatments using its established drug development platforms, focusing on bi‑specific, multi‑specific antibodies, and antibody‑drug conjugates (ADCs). SystImmune has multiple assets in various stages of clinical trials for solid tumor and hematologic indications. Alongside ongoing clinical trials, SystImmune has a robust preclinical pipeline of potential cancer therapeutics in the discover and IND‑enabling stages, representing cutting‑edge biologics development. We offer an opportunity for you to learn and grow while making significant contributions to the company's success. We’re hiring a Director to define, build, and lead our AI‑enabled small molecule design function. This is a hands‑on, individual‑contributor‑heavy role at the outset, where you will personally own strategy and execution, building core design workflows and delivering high‑quality candidate molecules before scaling a team around you. As the founding technical leader, you will collaborate closely with chemists, biologists, and computational scientists to integrate AI‑driven design into end‑to‑end drug discovery efforts at SystImmune. This position is located in Redmond, WA and requires an onsite presence. Key Responsibilities Own the design, development, and optimization of AI‑driven small molecule drug design pipelines, setting strategy and technical direction to predict molecular properties, enable virtual screening, and improve drug‑like characteristics across programs. Lead the application of advanced AI methodologies, including generative modeling, deep learning, and reinforcement learning, to generate novel small molecules and predict target interactions, with accountability for scientific rigor and translational impact. Oversee and advance AI‑based molecular docking capabilities (e.g., DiffDock), ensuring models are validated, scalable, and meaningfully improve binding affinity predictions, lead optimization, and virtual screening efficiency. Partner closely with medicinal chemistry, biology, DMPK, and computational biology leaders to integrate AI methods into end‑to‑end drug discovery workflows, ensuring seamless transition from computational design to experimental validation. Lead AI‑enabled efforts supporting drug manufacturing and developability, including optimization of synthesis routes, yield prediction, and manufacturability assessment for small molecule drug candidates. Direct large‑scale virtual screening strategies, leveraging AI models to explore expansive chemical space, prioritize compound libraries, and identify high‑quality lead candidates aligned with therapeutic objectives. Guide interpretation of computational and AI‑generated data, translating complex analyses into clear recommendations that inform decision‑making around pharmacokinetics, toxicity, efficacy, and compound progression. Drive the development, deployment, and evolution of AI‑based software tools and platforms, ensuring scalability, robustness, and usability across cross‑disciplinary scientific teams. Establish standards for data integration and insight generation from large‑scale chemical and biological datasets, enabling optimization of drug candidates for efficacy, safety, and pharmacokinetic profiles. Stay at the forefront of advances in AI and computational chemistry, particularly in AI small molecule generation, molecular docking, and virtual screening, and strategically apply emerging methods to continuously improve discovery productivity. Build, mentor, and lead a high‑performing small molecule design team, fostering an inclusive, high‑velocity culture while serving as a visible scientific leader internally and externally. Qualifications PhD or equivalent in Computational Chemistry, Bioinformatics, Biophysics, Machine Learning, or related field. 10+ years of experience applying computational chemistry and AI to small molecule drug design, with a proven track record advancing compounds into lead and clinical stages, including hands‑on expertise in AI‑based molecular generation, docking, virtual screening, and manufacturability‑aware design. Deep experience building and owning computational design platforms and workflows. Proven track record of applying AI/ML in drug discovery. Hands‑on expertise in structure‑based drug design, ligand‑based design, generative methods, and predictive modeling. Strong technical fluency in relevant tools and programming languages such as Python, R, or C++, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Excellent communicator with a bias for action and delivering results. Experience in antibody‑centric modalities and multi‑specific projects. Experience scaling teams and establishing operating rhythms in early programs. Prior success integrating design teams into cross‑disciplinary drug discovery organizations. Compensation & Benefits The expected base salary range for this position is $200,000 - $250,000 annually. Actual compensation will be based on a variety of factors, including but not limited to a candidate’s qualifications, experience, and skills. While most offers typically fall within the low to mid‑point of the range, we may extend an offer toward the higher end for exceptional candidates whose background and expertise exceeds the requirements of the role. SystImmune offers a comprehensive benefits package including: 100% paid employee premiums for medical/dental/vision, supplemental short‑term and long‑term disability, a 401(k) plan with a 50% company match of up to 3% and a vesting schedule of only 5 years, 15 PTO days per year, sick leave, 11 paid holidays, and additional benefits. We also provide a high‑performance culture that supports professional growth and innovation. Equal Opportunity Employer SystImmune is an Equal Opportunity Employer. We welcome diverse talent and encourage all qualified applicants to apply. #J-18808-Ljbffr SystImmune