Forward Deployed Engineer – Life Sciences & Pharma

EazyML, Recognized by Gartner, EazyML (www.EazyML.com) specializes in Responsible AI. Our solutions facilitate proactive compliance and sustainable automation and The company is associated with breakthrough startups like Amelia.ai.We’re seeking exceptional technical Forward Deployed Engineers to play a critical role in bridging our cutting-edge AI research with real-world deployments across pharmaceutical and life sciences enterprises. As a Forward Deployed Engineer, you will own the end-to-end technical strategy, execution, and delivery of complex agentic applications for use cases spanning drug discovery, clinical development, regulatory affairs, pharmacovigilance, and commercial operations — from early discovery through production deployment in GxP-regulated environments.What You'll DoPartner with Deployment Strategists to understand pharma and biotech customer needs — across R&D, clinical operations, regulatory, quality, and medical affairs — architect solutions, and develop transformative agentic applications for use cases such as clinical trial matching, protocol design support, adverse event triage, regulatory submission drafting, and medical literature synthesis.Architect and build complex agentic systems using state-of-the-art models, orchestrating sophisticated LLM workflows over clinical, scientific, and regulatory data, and integrating deeply with enterprise pharma infrastructure (CTMS, EDC, LIMS, ELN, safety databases, and document management systems).Collaborate with research teams to adapt and fine-tune models for customer-specific needs — including domain adaptation on biomedical literature, clinical notes, and regulatory corpora — contributing to our internal codebase for inference, fine-tuning, and evaluation.Own end-to-end deployments across hybrid environments (public cloud, VPC, and on-premises), ensuring production-grade scalability, performance, and reliability while meeting the validation, auditability, and data privacy requirements of GxP, HIPAA, and 21 CFR Part 11.Shape and scale the Forward Deployed Engineering organization by defining playbooks, best practices, technical standards, and mentorship — including reusable patterns for computer system validation (CSV/CSA) and model risk documentation — to support team growth.What We're Looking ForStrong software engineering background with experience shipping production-grade systems (Python, TypeScript), ideally with some exposure to regulated or compliance-sensitive industries (pharma, biotech, healthcare, financial services).Proven track record of deploying enterprise software in cloud or hybrid environments using modern DevOps practices (Docker, Kubernetes, and CI/CD), including in validated or audit-controlled infrastructure.Deep understanding of machine learning concepts and hands-on experience with modern AI stacks, including vector databases, RAG pipelines over scientific/clinical corpora, agent orchestration, evaluations, and fine-tuning.6+ years of software engineering experience, including 2+ years in a technical leadership capacity delivering AI-driven enterprise solutions (e.g., Lead Forward Deployed Engineer, Tech Lead, or Engineering Manager).Demonstrated ability and interest to work in customer-facing environments with pharma stakeholders — clinical, regulatory, quality, and IT — understanding user needs, architecting solutions for real business and scientific problems, and delivering tangible outcomes.Self-starter with high agency and ownership, excelling in fast-paced startup environments where playbooks are still being written — including navigating the ambiguity of first-of-a-kind AI deployments in regulated settings.Working familiarity with pharma/life sciences data standards and systems is a strong plus: CDISC (SDTM/ADaM), HL7 FHIR, OMOP, Veeva Vault, Medidata Rave, or pharmacovigilance platforms such as Argus.Understanding of GxP principles (GCP/GMP/GLP), 21 CFR Part 11, and HIPAA as they apply to computer system validation and handling of protected health information (PHI) is a strong plus.Exposure to real-world data (claims, EHR, registries), bioinformatics/genomics pipelines, or health economics and outcomes research (HEOR) is a plus but not required.What We OfferWe believe that to make intelligence open and accessible to all, you need to start at the foundation. Joining EazyML means building from the ground up as part of a talent-dense team applying AI to some of the highest-stakes, highest-impact problems in pharma and life sciences — accelerating the pace at which new therapies reach patients.We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported. Top-tier compensation: salary structured to recognize and retain our talent globally.