Forward Deployment Engineer

Location: Barcelona, Spain (Hybrid)Type of Hiring: ContractJob Description:About the RoleWe are looking for a Forward Deployment Engineer (FDE) to sit at the intersection of AI engineering and customer success. You will work directly with pharma clients to deploy, integrate, and scale AI-powered solutions - translating complex technical capabilities into real-world workflows. This is a hands-on, client-facing engineering role where you own outcomes, not just deliverables.What You’ll DoPartner with pharma clients from pilot to production - leading technical onboarding, integration, and go-liveBuild and maintain API integrations between AI platforms and client systems (EHR, CTMS, regulatory, lab, and commercial systems)Deploy AI/ML models and inference services on cloud infrastructure (AWS, Azure, or GCP) - ensuring reliability, security, and scalabilityTranslate domain-specific pharma workflows (clinical trials, pharmacovigilance, regulatory submissions, drug discovery) into technical requirementsDebug integration issues in production, triage model behavior, and coordinate with internal engineering teams on fixesDevelop reusable reference architectures, integration playbooks, and technical documentationAct as a trusted technical advisor to client engineering and IT teamsSurface product feedback from the field to inform the roadmapWhat You Bring4+ years of software or integration engineering experienceStrong proficiency in Python; experience with REST API design, OAuth, and webhook integrationsHands-on cloud deployment experience (AWS, Azure, or GCP) - containers, serverless, IAM, networkingFamiliarity with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and prompt engineering basicsHands-on data engineering experience with Snowflake or Databricks - data pipelines, transformations, and working with large structured/unstructured datasetsExperience with CI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation, or similar)DomainWorking knowledge of the pharmaceutical value chain - clinical development, regulatory affairs (FDA/EMA), pharmacovigilance, or commercial operationsFamiliarity with pharma data standards (CDISC, HL7/FHIR, MedDRA) is a strong plusUnderstanding of pharma compliance and data privacy requirements (21 CFR Part 11, GxP, HIPAA)Soft SkillsComfortable in ambiguous, fast-moving client environmentsStrong communicator - able to explain technical concepts to non-technical stakeholdersNice to HaveExperience with RAG pipelines, vector databases, or document AI (OCR, NLP)Background in a pharma/biotech company or a consulting firm serving the life sciences sectorFamiliarity with platforms like Veeva, Medidata, or Oracle Health SciencesWhat Success Looks LikeIn the first 30 days, you’re embedded with a client team and have shipped at least one integration. In 90 days, you’re running deployments independently and have become the go-to technical resource for your accounts.#J-*****-Ljbffr

4+ years of software or integration engineering experience Strong proficiency in Python; experience with REST API design, OAuth, and webhook integrations Hands-on cloud deployment experience (AWS, Azure, or GCP) - containers, serverless, IAM, networking Familiarity with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and prompt engineering basics Hands-on data engineering experience with Snowflake or Databricks - data pipelines, transformations, and working with large structured/unstructured datasets Experience with CI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation, or similar) Domain Working knowledge of the pharmaceutical value chain - clinical development, regulatory affairs (FDA/EMA), pharmacovigilance, or commercial operations Familiarity with pharma data standards (CDISC, HL7/FHIR, MedDRA) is a strong plus Understanding of pharma compliance and data privacy requirements (21 CFR Part 11, GxP, HIPAA) Soft Skills Comfortable in ambiguous, fast-moving client environments Strong communicator - able to explain technical concepts to non-technical stakeholders Nice to Have Experience with RAG pipelines, vector databases, or document AI (OCR, NLP) Background in a pharma/biotech company or a consulting firm serving the life sciences sector Familiarity with platforms like Veeva, Medidata, or Oracle Health Sciences