Sr. AI Developer, Engineering

๐Ÿข EVERSANA ยท all EVERSANA jobs
๐Ÿ“ United States
๐Ÿ’ฐ USD 122,000 - 207,000 / annual
๐Ÿ“… Posted 2026-08-23 ยท via Himalayas
๐Ÿท AI-Engineering,Solutions-Architect,Enterprise-Software-Development,Technical-Consulting,Generative-AI,Senior-AI-Engineer,Senior-AI-Software-Engineer,Senior-AI-Engineering,Senior-Software-AI-Engineer,Senior-AI-Developer,Senior-AI-ML-Engineer,Senior-AI-ML-Developer,Senior-Applied-AI-Engineer
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The Senior AI Agency 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 the responsibilities of a senior software engineer, solutions architect, and client-facing technical consultant. The individual leads technical discovery with clients, translates business requirements into scalable technical solutions, develops integrations and AI workflows, and partners across product, engineering, data, security, and delivery teams to bring production-ready AI solutions to market.

The ideal candidate possesses deep expertise in modern software engineering, cloud-native architecture, enterprise integrations, and generative AI technologies, along with the communication skills needed to engage both technical teams and executive stakeholders.

ESSENTIAL DUTIES AND RESPONSIBILITIES:
Our employees are tasked with delivering excellent business results through the efforts of their teams. These results are achieved by:
Client Discovery & Technical Leadership

- 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.

Solution Architecture & Engineering

- 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.

Enterprise Integrations & Data Engineering

- 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.

Cloud Infrastructure, Deployment & Operations

- Develop cloud-native solutions with a preference for Google Cloud Platform.

- Implement CI/CD pipelines and auto

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