Sr. AI Developer, Engineering

EVERSANA is a global, full-service marketing agency network serving the life sciences industry through creative, media, enterprise solutions, and data analytics services. The Senior AI Developer, Engineering designs, builds, and deploys enterprise-grade AI solutions integrating generative AI, workflow automation, compliance controls, and business systems, while leading technical discovery, solution architecture, integrations, and production deployments.

Responsibilities:

• Lead technical discovery sessions with client business, IT, architecture, security, data, and operations teams
• Translate business objectives, workflows, and operational challenges into technical requirements, architecture designs, and implementation plans
• Assess enterprise application landscapes, integration requirements, data environments, security constraints, and operating models
• 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
• Identify technical risks, dependencies, assumptions, and mitigation strategies early in engagements
• Develop technical prototypes and proofs of concept to validate solution feasibility and accelerate decision-making
• Design end-to-end solutions that connect AI Agency capabilities with client systems, data sources, content repositories, workflows, and approval environments
• Build and configure production-quality integrations using APIs, webhooks, event-based patterns, secure file exchanges, connector frameworks, and enterprise integration platforms
• Develop client-specific configuration and deployment assets while preserving the integrity of the shared platform architecture
• Contribute hands-on code across backend services, integration components, data pipelines, AI workflows, and supporting user experiences
• Design and implement AI-enabled workflows using large language models, retrieval-augmented generation, agent orchestration, structured outputs, evaluation frameworks, and human approval checkpoints
• Implement authentication, authorization, identity federation, secrets management, data mapping, error handling, observability, and audit requirements
• Create technical prototypes when needed to validate feasibility, reduce ambiguity, or accelerate client decision-making
• Support the transition from prototype to stable, supportable production deployment
• Design, build, and maintain integrations using APIs, webhooks, event-driven architectures, secure file exchanges, and enterprise integration platforms
• Develop system connectors to enterprise platforms including: Veeva Vault / PromoMats; Salesforce Marketing Cloud; SharePoint; Adobe Experience Cloud; Snowflake; BigQuery; Vertex AI
• Build and maintain data pipelines supporting reporting, analytics, and AI workflows
• Design data mapping, transformation, validation, and synchronization processes
• Partner with data engineering teams to support ETL/ELT and analytics initiatives
• Develop cloud-native solutions with a preference for Google Cloud Platform
• Implement CI/CD pipelines and automated deployment processes
• Build and maintain containerized applications using Docker and Kubernetes
• Ensure application reliability through monitoring, logging, alerting, and observability practices
• Maintain high standards of testing, code quality, scalability, and operational excellence
• Support production troubleshooting, performance optimization, and incident resolution
• Modeling inclusive behaviors and proactively managing bias
• All other duties as assigned*

Requirements:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience
• 9+ years of experience in software engineering, solution engineering, technical consulting, platform implementation, or related engineering roles
• 5+ years designing and deploying production cloud-based AI, data, or enterprise application solutions
• Advanced programming skills in Python and at least one additional modern language such as JavaScript/TypeScript, C#, Java, or .NET
• Significant experience designing:
  • APIs
  • Data pipelines
  • Event-driven architectures
  • Enterprise integrations
  • Authentication and security frameworks
  • Distributed systems
• Hands-on experience with generative AI technologies including:
  • LLMs
  • Prompt engineering
  • RAG
  • Embeddings
  • Vector databases
  • Agent orchestration
  • AI evaluations
  • Observability and guardrails
• Experience with Git, CI/CD, automated testing, containers, and cloud-native development practices
• Strong communication, consulting, and stakeholder management skills with the ability to influence