Position SummaryWe are seeking a highly accomplished Lead AI Engineer with 10 years of total IT experience to join our team. In this strategic, hands-on leadership role, you will serve as the senior technical authority responsible for architecting and delivering enterprise-grade Agentic AI solutions that fundamentally transform Finance and Corporate Affairs operations at scale.
As the engineering anchor of a high-performing, cross-functional team, you will drive the full software development lifecycle (SDLC) from initial architecture through production delivery - while establishing AI platform standards, leading rigorous technical reviews, and actively mentoring a team of senior and mid-level engineers. Your contributions will directly shape intelligent automation capabilities for our business.
This is a high-visibility, high-impact role at the intersection of advanced AI engineering and enterprise domain expertise. We are looking for a leader who combines deep technical mastery with the ability to communicate complex architectural decisions to executive stakeholders - someone who builds production AI systems that solve real-world, mission-critical business challenges.
Required Qualifications- 10 years of total IT experience, with a significant portion in senior or lead engineering roles delivering enterprise-scale solutions across the full SDLC.
- Demonstrated technical leadership experience - driving architecture decisions, managing engineering teams, conducting design reviews, and owning delivery outcomes in a cross-functional, matrixed environment.
- Deep expertise in designing and delivering enterprise Agentic AI applications using Python, LangChain, LangGraph, and Azure OpenAI - building autonomous, multi-step AI systems with durable state management and fault-tolerant execution.
- Strong domain knowledge in Finance and Corporate Affairs domain, including a thorough understanding of complex document structures such as contracts, compliance filings, regulatory submissions, matter intakes, and legal correspondence - enabling accurate AI-driven ingestion, classification, and routing at scale.
- Hands-on experience with Intake workflows automation - designing automated intake systems that capture, classify, and triage, and route intake requests through intelligent AI pipelines.
- Proven experience with SAP integrations - connecting AI-driven workflows with SAP ERP modules.
- Expertise designing multi-agent state-machine architectures with LangGraph - implementing supervisor, router, and specialist agent patterns with inter-agent handoff protocols and shared memory and context management across long-running workflows.
- Strong proficiency building production-grade RAG (Retrieval-Augmented Generation) pipelines incorporating vector embeddings, semantic chunking, hybrid search, and multi-modal knowledge retrieval for legal, compliance, and procurement use cases.
- Hands-on experience engineering full-stack AI solutions on Azure Cloud - including Azure OpenAI, Azure Kubernetes Service (AKS), Azure API Management (APIM), Azure Blob Storage, and Azure Cognitive Services - within secure, regulated enterprise architectures.
- Experience designing and maintaining CI/CD pipelines using GitHub Actions, Docker containerization, and AKS deployments - including model integration testing, vulnerability scanning, and event-driven architectures for high-throughput, scalable AI workloads.
- Demonstrated ability to implement enterprise-grade AI security controls - including prompt injection mitigation, autonomous agent guardrails, role-scoped tool access policies, and output validation frameworks aligned to regulatory and compliance standards.
- Experience architecting and leading Procurement and ERP system integrations with AI workflows - spanning sourcing events, supplier onboarding, purchase requisitions, and spend analytics automation.
- Proven ability to orchestrate long-running, fault-tolerant AI agent workflows using Temporal - including activity-based decomposition, saga patterns, and durable execution pipelines designed for enterprise-scale production reliability.
- Experience developing conversational AI interfaces using Azure Bot Services, integrated with Microsoft Teams and enterprise identity platforms, to surface AI agent capabilities directly within organizational collaboration workflows.
- Strong proficiency in SQL and relational query design within Agentic AI systems - enabling AI agents to dynamically construct, execute, and interpret structured database queries as part of automated reasoning, data retrieval, and decision-making workflows.
- Hands-on experience leveraging Google Vertex AI for enterprise-grade external and internet search capabilities - integrating Google's grounding and search APIs within Agentic AI workflows to enable real-time, web-scale knowledge retrieval, fact augmentation, and dynamic external data sourcing beyond internal knowledge bases.
Preferred Qualifications- Experience architecting Model Context Protocol (MCP) servers to expose enterprise systems - including internal APIs, databases, and enterprise tools - as AI-consumable tool chains enabling real-time agent-to-service integration across distributed platforms.
- Experience building and deploying custom Speech-to-Text (STT) services - converting audio recordings into structured, actionable text with hallucination detection - and custom OCR services for extracting structured content from scanned contracts and unstructured document attachments.
- Proficiency designing Agentic AI frontend experiences using React.js - including real-time agent status dashboards, multi-step workflow visualizers, streaming LLM output panels, and tool-execution trace viewers for operational visibility.
- Experience integrating Agentic AI decision outputs with ServiceNow - automating ticket creation, approval routing, incident enrichment, and ITSM workflow triggers driven by AI agent actions.
- Track record of developing and publishing shared internal Python libraries for AI agent tooling, vector embedding utilities, and platform abstractions - driving engineering reusability, consistency, and accelerated delivery across distributed AI teams.
EducationMaster's degree in computer scienceAnticipated Weekly Hours40
Time TypeFull time
Pay RangeThe typical pay range for this role is:
$92,700.00 - $185,400.00
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.
Great benefits for great peopleWe take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.
This full-time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well-being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.
Additional details about available benefits are provided during the application process and on Benefits Moments.
We anticipate the application window for this opening will close on: 08/07/2026
