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EVERSANA INTOUCH is a global marketing agency network serving the life sciences industry, part of the fully integrated EVERSANA commercialization platform. The Senior AI Engineer designs, builds, and deploys enterprise-grade AI solutions that connect generative AI, workflow automation, compliance controls, and business systems to accelerate pharmaceutical and healthcare marketing operations.
This role combines senior software engineering, solutions architecture, and client-facing technical consulting. You will lead technical discovery with clients, translate business requirements into scalable technical solutions, develop integrations and AI workflows, and partner across product, engineering, data, security, and delivery teams to bring production-ready AI solutions to market.
Key responsibilities include:
• Client Discovery & Technical Leadership: Lead technical discovery sessions with client business, IT, architecture, security, data, and operations teams. Translate business objectives and operational challenges into technical requirements and architecture designs. Serve as a trusted technical advisor to clients and internal stakeholders. Communicate complex AI, data, platform, and integration concepts to both technical and executive audiences.
• Solution Architecture & Engineering: Design end-to-end solutions connecting AI capabilities with client systems, data sources, content repositories, and workflows. Build production-quality integrations using APIs, webhooks, event-based patterns, and enterprise integration platforms. Develop client-specific configuration and deployment assets. Contribute hands-on code across backend services, integration components, data pipelines, and AI workflows. Design AI-enabled workflows using large language models, retrieval-augmented generation, agent orchestration, and structured outputs.
• Enterprise Integrations & Data Engineering: Design and build integrations with enterprise platforms including Veeva Vault, Salesforce Marketing Cloud, SharePoint, Adobe Experience Cloud, Snowflake, BigQuery, and Vertex AI. Develop and maintain data pipelines supporting reporting, analytics, and AI workflows. Partner with data engineering teams on ETL/ELT initiatives.
• Cloud Infrastructure & Operations: Develop cloud-native solutions on Google Cloud Platform. Implement CI/CD pipelines and automated deployment processes. Build containerized applications using Docker and Kubernetes. Ensure reliability through monitoring, logging, alerting, and observability practices.
Required qualifications: Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience. 9+ years in software engineering, solution engineering, technical consulting, or platform implementation. 5+ years designing and deploying production cloud-based AI, data, or enterprise application solutions. Advanced Python programming skills.
