Digital Agent Technology Specialist

McKesson•Mississauga, ON

3d•$81,500 - $108,600•Hybrid

About The Position

McKesson Technology is rapidly expanding its use of intelligent digital agents to automate complex customer interactions across voice, chat, and email, and we're looking for an engineer who's ready to build what's next. The Senior Digital Agent Engineer is a hands-on technical role responsible for designing, building, and validating AI-powered digital agents on our AI conversational platform. Working across voice, chat, and email channels, this engineer will deliver autonomous agent experiences that handle customer intents for supply chair, patient care, and technical solutions. The Senior Digital Agent Engineer operates at the intersection of conversational AI, enterprise integration, and contact center technology partnering closely with business stakeholders, solution architects, and platform engineers to bring intelligent, reliable agents from design to production.

Requirements

Advanced knowledge proficiency in intelligent automation, process automation, and deployment automation
4+ years of experience developing conversational AI solutions on enterprise-grade platforms such as Sierra.AI, Google CCAI, Agentforce, Nuance, or comparable
Hands-on experience working with large language models (LLMs) / foundation models including prompt engineering, model selection, and evaluation of model outputs and quality
Demonstrated experience building and deploying digital agents across multiple channels (voice, chat, and/or email) in a production environment
Proficiency integrating AI platforms with enterprise systems via REST APIs, MuleSoft, or similar middleware and integration frameworks
Familiarity with CRM platforms (Salesforce preferred) and ERP systems (SAP preferred) in the context of agent-driven transaction execution
Experience with CCaaS platforms such as Five9 or Genesys, including understanding of call routing, SIP/PSTN flows, and agent handoff patterns
Solid understanding of NLU/NLP concepts including intent classification, entity extraction, dialogue management, and confidence thresholds
Experience performing system integration testing and documenting test cases, results, and defect tracking
Strong written and verbal communication skills with the ability to collaborate across technical and non-technical stakeholders

Nice To Haves

Experience with LLM evaluation, retrieval-augmented generation (RAG), or agentic orchestration in a production setting
Hands-on experience with Sierra.AI, specifically
Experience in healthcare distribution, pharmaceutical, or supply chain industries
Familiarity with workforce management / quality management platforms (e.g., Verint or similar workforce engagement / quality management platforms)
Exposure to Agile/Scrum delivery methodologies and sprint-based development

Responsibilities

Design and develop digital agents on the AI platform across voice, chat, and email channels, building conversation flows, intent handling, slot filling, and fallback logic that deliver accurate, end-to-end customer experiences
Partner with the AI Solution Owner and Engineering Lead to author Solution Design Documents (SDDs) that meet McKesson Technology architecture and compliance standards prior to build
Integrate digital agents with enterprise systems including Five9, Genesys, Salesforce, MuleSoft, SAP, web portal, and Athena, ensuring reliable data exchange and transaction execution across platforms
Execute System Integration Testing (SIT) to validate agent behavior, integration responses, and edge case handling before handoff to Quality Assurance; document test results and resolve defects identified during testing
Participate in code reviews, providing and receiving constructive technical feedback to maintain code quality, consistency, and adherence to engineering standards before promoting changes to higher environments
Collaborate with business partners, Product Owners, and the Contact Center Transformation Lead to translate business requirements and customer journey designs into technically sound agent implementations
Apply and evaluate large language models within agent workflows including prompt design, retrieval, and output evaluation to improve accuracy, safety, and reliability
Support the tuning and optimization of digital agents post-launch by analyzing conversation logs, identifying failure points, and implementing improvements in partnership with the AI Optimization team
Maintain technical documentation including SDDs, integration specifications, and configuration records to ensure continuity and supportability across the team