EVERSANA INTOUCH 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 designs, builds, and deploys enterprise-grade AI solutions, leads client technical discovery, and develops scalable integrations, AI workflows, cloud infrastructure, and production-ready software for pharmaceutical and healthcare marketing operations.

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

Java Application Developer

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