Digital Solution Architect, flexible working

Elucidata is an AI Solutions Tech Data-centric AI company on a mission to make life sciences AI-ready. Headquartered in San Francisco with a 120+ member team across the US and India, we’re building the future of data-centric AI for drug discovery. Our flagship AI-Agentic powered platform, Polly, helps research teams wrangle, harmonize, and analyze massive volumes of biomedical data, accelerating discoveries and making precision medicine a reality. Recognized by Fast Company as the “Most Innovative Biotech Company of 2024,” Elucidata partners with 25+ leading organizations, including Pfizer, Novo Nordisk, Google DeepMind, Alnylam Therapeutics, and the Bill & Melinda Gates Research Institute. With over 200 data products and AI solutions co-developed by 100+ domain experts, we’ve helped our partners achieve 4X faster R&D milestones and contribute to 16 therapies advancing toward FDA approval. At Elucidata, you’ll work at the intersection of AI, biology and impact while solving real-world challenges that accelerate the journey from data to discovery. We are looking for an experienced Solutions Scientist passionate about applying agentic and GenAI automation in life sciences. The ideal candidate bridges AI system design with biological insight. The ideal candidate will be able to work with both R&D and business teams to turn bottlenecks and manual workflows into intelligent, automated workflows. This role is at the intersection of AI architecture, bioinformatics workflows, and solution design,a great opportunity for someone who enjoys working across technical and scientific boundaries to build high-impact AI solutions. Explore and evaluate opportunities across bioinformatics and R&D workflows where agentic automation can accelerate analysis, reduce manual steps, or enhance decision-making. Work closely with R&D, bioinformatics, and marketing teams to create technical materials, case studies, and demo assets showcasing AI-driven automation and workflow intelligence. Break down customers' scientific or operational workflows into components identifying which steps can be automated, which benefit from LLM intelligence, and which require expert input and design scalable, modular systems around them. Translate complex AI workflows into clear, business-aligned narratives for clients and stakeholders; Educational Background: Master's in Computer Science, Bioinformatics, Computational Biology, or a related technical discipline. Experience: Minimum of 3-4 years of ML or AI solution building experience, with at least 1 year in drug discovery or healthcare related agentic automation workflow experience. Hands-on experience in typical bioinformatics workflows from finding datasets (e.g., GEO, TCGA, cbioportal, CellxGene etc) to exploratory data analysis, differential expression, pathway analysis, and report generation. Strong AI System Thinking:Ability to design AI-driven systems that balance automation, intelligence, and human oversight; Curious & Versatile: Comfortable working across diverse data types (omics, clinical patient data, assay data) and eager to explore new domains. Opportunity to shape the future of biomedical data ecosystems by building partnerships at the frontier of science and healthcare. Work with global leaders and contribute to data-driven drug discovery. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, caste, citizenship, marital status, disability, gender identity, or Veteran status. Competitive compensation including ESOPs Unlimited vacation and holiday time off Hybrid work environment (3 days in office) for leading the charge in making life sciences data AI-ready. ~ - hear what our team says about building the future of TechBio together. ~ - celebrating innovation at the intersection of AI and biology. ~ - Richard Kibbey who are redefining what’s possible in data-driven drug discovery. ~ - driving AI adoption in oncology research. ~ - recognised for cutting-edge innovation in biomedical AI. ~ - to see how we’re advancing data-centric AI for life sciences.