Forward Deployed Engineer - Generative & Agentic AI

myhrabc; United States; On-site; USD 170,000 - 210,000; Full time

Job summary

Cencora is seeking a Forward Deployed Engineer to embed with business units and deliver production-grade Generative and Agentic AI solutions in days. You will scope problems with the business, build within their systems and data, and feed learnings back to our AI platform for faster future engagements.

You’ll lead with stakeholders, design API-first integrations, and apply MLOps practices to keep deployments reliable in production, while communicating complex tradeoffs to executives and

Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
• 8+ years of overall software engineering/IT experience.
• 3+ years building Generative AI / Agentic AI systems.
• Strong expertise in Python and modern AI development frameworks.
• Hands-on with LLMs and multiagent orchestration frameworks (LangGraph, AutoGen, Semantic Kernel).
• Deep understanding of RAG architectures, vector databases, and embedding models.
• Experience with Azure/AWS/GCP, including native AI services.
• Proven MLOps/LLMOps: CI/CD, containerization, observability, evaluation frameworks.
• Comfortable embedding with business teams, onsite engagement as needed.
• Excellent communication skills for executives and engineers.

Responsibilities

• Embed with business units to understand workflows and data firsthand.
• Scope and ship Generative AI / Agentic AI solutions inside real systems and data in days to weeks.
• Build RAG pipelines, apply prompt engineering, and stand up eval frameworks for trust.
• Design and build API-first integrations that connect AI into enterprise systems.
• Translate business needs into technical specs and tradeoffs for stakeholders.
• Lead stakeholder workshops and proactively flag risks.
• Stay engaged through stabilization and adoption, fix issues in production.
• Feed improvements back into the shared AI platform and toolkit.
• Apply MLOps/LLMOps to keep deployed solutions reliable.

Skills

Python

Generative AI

LLMOps

Stakeholder workshops

Communication

Education

Bachelor's or Master's in Computer Science/AI/Data Science

Tools

Databricks

Azure

LangGraph

AutoGen

Semantic Kernel

OpenAI/Claude/GPT

Ragas

Job description

Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere.

Job Details

About the Role

We are seeking a Forward Deployed Engineer (FDE) to embed directly with business units and stakeholder teams, turning real-world problems into working, production grade Generative and Agentic AI solutions in days and weeks, not months. This is a hands-on, high ownership role that blends software engineering, solution architecture, and consulting: you scope the problem alongside the business, build the solution inside their actual systems and data, and feed what you learn back into our shared AI platform, so every future engagement moves faster. If you thrive in ambiguity, love shipping fast, and want your code to matter on day one, this role is built for you.

Key Responsibilities

• Embed directly with business units and stakeholder teams to understand their workflows, data, and pain points firsthand, not from a spec document.
• Scope and ship working Generative AI / Agentic AI solutions (POCs, MVPs, and production features) directly inside the business's real systems and data, in days to weeks cycles.
• Build RAG pipelines, apply prompt engineering, and stand-up evaluation frameworks (“evals”) that prove a solution is accurate enough to trust before going live.
• Design and build API first integrations that connect AI capabilities into existing enterprise systems and workflows.
• Translate ambiguous business needs into technical specs and translate technical tradeoffs back into language executives and business stakeholders can act on.
• Lead stakeholder workshops, present progress transparently, and proactively flag risks before they become blockers.
• Stay engaged through stabilization and adoption and fixing issues as they surface in the real world, not just at handoff.
• Feed improvements, reusable components, and lessons learned back into the shared AI platform and toolkit so every future engagement benefits.
• Apply MLOps/LLMOps practices (CI/CD, monitoring, model/agent lifecycle management) to keep deployed solutions reliable in production.

Our Tech Stack

Databricks platform, Unity Catalog, Delta Lake, Databricks Apps, and Databricks AI Gateway for model routing and governance. Microsoft Azure, including Azure AI Foundry for model deployment and orchestration. Multi LLM provider access - Anthropic Claude, OpenAI (GPT & Codex), and other foundation models.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
• 8+ years of overall software engineering / IT experience.
• 3+ years of hands-on experience building Generative AI / Agentic AI systems.
• Strong expertise in Python and modern AI development frameworks.
• Practical experience with LLMs (OpenAI, Claude, Gemini, Llama, or open weight models) and multiagent orchestration frameworks (LangGraph, AutoGen, or Semantic Kernel).
• Deep understanding of RAG architectures, vector databases, and embedding models.
• Experience with at least one major cloud platform (Azure, AWS, or GCP), including native AI services.
• Proven experience with MLOps/LLMOps: CI/CD, containerization, observability, and evaluation frameworks.
• Comfortable embedding directly with business or customer teams, including onsite engagement as needed.
• Excellent communication skills - able to run stakeholder workshops and present to both executives and engineers in the same day.
• Demonstrated ability to own a solution end-to-end in ambiguous, fastmoving environments, from scoping through production.

Preferred Qualifications

• Prior forward deployed, consulting, or solutions architecture experience.
• Familiarity with Model Context Protocol (MCP) and emerging AI agent ecosystems.
• Experience building evals with tools like Ragas, Lang Smith, or custom harnesses.
• Business or domain fluency in a regulated industry (healthcare, finance, or government) where data sensitivity and compliance shape the solution.
• Track record of building reusable frameworks or components that scale across multiple engagements.

HEALTHCARE DOMAIN PREFERENCE

We strongly prefer candidates who bring healthcare industry knowledge alongside AI expertise. Forward Deployed Engineers on our team embed directly with healthcare distribution and specialty pharmacy business units - experience with healthcare distribution, specialty pharma data, or healthcare EMR/EHR systems (HL7, FHIR, claims, ND level data) is a significant advantage in building trust and shipping solutions that fit really clinical and operational workflows.

What Cencora offers

We provide compensation, benefits, and resources that enable a highly inclusive culture and support our team members' ability to live with purpose every d