Senior AI Engineer

Adelphi Group•New York, NY

1d•$145,000 - $185,000•Hybrid

About The Position

The Senior AI Engineer, Agentic Solutions & Workflows is a hands-on technical role responsible for designing, building, testing, deploying, and optimizing AI-powered agents, workflows, and automation solutions. Working with AI leadership, solution architects, strategy and delivery teams, scientific specialists, and client-facing teams, the engineer translates business needs into scalable AI-enabled solutions. The work applies generative and agentic AI across Medical Affairs, Publications, Scientific Communications, Commercial Medical Communications, and other organizational workflows. The role covers the solution lifecycle from use-case discovery and design through prototyping, testing, deployment, and ongoing optimization, with an initial focus on building individual agents in partnership with the AI solutions architect and business-unit specialists. The position includes developing reusable agents, workflow components, prompts, and AI accelerators; applying enterprise AI platforms, language models, APIs, and related technologies; and aligning solutions with architecture, security, governance, privacy, and platform standards. The engineer works with business and delivery teams to discover and scope use cases, prototype solutions, evaluate outputs, refine deployed agents, support integrations, and prepare documentation and training materials. Initial use cases include research and synthesis, scientific content creation and transformation, congress content development, extraction, document and slide development, summarization, quality and consistency checking, compliance support, knowledge retrieval, and process automation. Omnicom Health Medical Communications supports pharmaceutical, biotechnology, and healthcare clients across the lifecycle of their assets, from early discovery through commercialization. The company describes itself as a global leader in publications, medical affairs, regulatory consultation, and AOR medical communications. The posting states that employees are required to work in the office at least three days per week, to the extent permissible by local law, unless their agency or manager directs additional in-office days.

Requirements

Demonstrated hands-on experience building solutions using generative AI and large language models.
Experience designing and developing AI agents, agentic workflows, or LLM-powered applications.
Strong understanding of prompt engineering and LLM behavior.
Experience with APIs and systems integration.
Ability to translate business requirements into practical technical solutions.
Experience taking solutions from prototype through testing and production deployment.
Strong problem-solving skills and ability to troubleshoot technical issues and AI output-quality challenges.

Nice To Haves

4–7+ years of experience in software engineering, AI engineering, automation, data engineering, or related technical roles.
Experience working with Python and/or other relevant programming languages.
Familiarity with Retrieval-Augmented Generation (RAG), vector search, embeddings, and enterprise knowledge architectures.
Experience with Microsoft Azure AI, Copilot Studio, Power Platform, or similar enterprise ecosystems.
Experience with OpenAI, Anthropic, Google, or other foundation model APIs.
Familiarity with multi-agent architectures and workflow orchestration frameworks.
Experience working with SharePoint, Microsoft Teams, and enterprise knowledge repositories.
Healthcare, pharmaceutical, life sciences, or other regulated-industry experience.
Understanding of Commercial, Medical Affairs, Publications, or medical communications workflows.

Responsibilities

Translate complex business processes into AI-enabled workflows and identify where AI, automation, and human intervention should be applied.
Develop reusable agents, workflow components, prompts, and AI accelerators that can scale across teams and accounts.
Build solutions using enterprise AI platforms, large language models, APIs, retrieval-augmented generation, and related AI technologies.
Collaborate with AI Architects to align solutions with enterprise architecture, security, governance, data privacy, and platform standards.
Partner with Commercial, Medical Affairs, Publications, Scientific Services, Strategy, Digital, and client teams to identify and scope high-value AI use cases.
Facilitate workflow discovery sessions to understand current processes, pain points, inputs, outputs, decision points, and opportunities for AI enablement.
Rapidly prototype and test AI solutions, incorporating feedback from subject matter experts and end users.
Establish systematic approaches for testing and evaluating AI output accuracy, consistency, reliability, and adherence to requirements.
Optimize prompts, agent instructions, knowledge sources, retrieval strategies, and workflow logic to improve solution performance.
Troubleshoot technical and output-quality issues and refine deployed agents using user feedback and performance information.
Support integration of AI solutions with knowledge bases, document repositories, APIs, and enterprise platforms where appropriate.
Develop documentation, user guidance, and training materials to support deployment and adoption.
Partner with Digital project managers and delivery teams to move solutions from prototype through testing, controlled release, deployment, and ongoing maintenance.
Monitor developments in generative AI, agentic AI, LLMs, and automation technologies and identify opportunities to apply them to client and agency workflows.