Principal Enterprise Software Engineer

C T Corporation System (DE); Kennesaw (GA); Presencial; USD 180.000 - 260.000; Jornada completa

Descripción de la vacante

Wolters Kluwer is seeking a hands-on Principal AI Solutions Engineer in our AES Team to architect, build, and deploy enterprise-scale AI solutions on our next-generation AI platform. You will translate business needs into AI-driven workflows, design agents and orchestrations, and partner with customers, security, and operations to scale impact across the enterprise.

This role requires deep expertise in AI, cloud-native patterns, and governance, with a track record of production LLM applications

Formación

• Experience building production LLM applications.
• Ability to translate business processes into AI-driven workflows.
• Experience designing and governing AI deployments with risk controls.
• Strong cloud platform experience (Azure/AWS/GCP).

Responsabilidades

• Translate business processes into AI use cases solved via agents, orchestrations, skills, and plugins.
• Lead design and delivery of end-to-end AI solutions integrating process engineering with business logic.
• Architect agentic systems with intent-driven decision-making and controlled execution.
• Accelerate AI adoption by democratizing capabilities across teams.
• Mentor engineering teams in AI solution design patterns and governance.
• Shape the AI platform roadmap based on customer needs and emerging patterns.
• Collaborate on AI governance, compliance, and risk controls for deployments.

Conocimientos

AI solution design

Cloud platforms

Python

Agentic systems

LLM frameworks

Orchestrations

Herramientas

LangChain

LlamaIndex

OpenAI SDK

Anthropic SDK

Plugins

Descripción del empleo

Wolters Kluwer is seeking a hands-on Principal AI Solutions Engineer in our Architecture & Engineering Services (AES) Team to architect, build, and deploy enterprise-scale AI solutions on our next-generation AI platform. Working within our Engineering team and collaborating closely with customers, Cloud Operations, Security, Compliance, and business stakeholders, this principal engineer will drive AI-powered transformation initiatives across the enterprise.

Our Principal AI Solutions Engineer will lead the development of intelligent, cloud-native, agentic AI solutions that operationalize decision‑making and process automation across the organization. The role requires deep expertise in designing AI agents, composing orchestrations, engineering reusable skills, and building extensible plugins that solve complex business problems. Beyond architecting AI systems, this engineer will demonstrate thought leadership in translating business processes into AI‑driven workflows and will play a key role in evolving our AI platform roadmap.

Key Responsibilities

• Translate business processes and operational workflows into AI use cases solved via agents, orchestrations, skills, and plugins on our platform
• Lead the design and delivery of end‑to‑end AI solutions that integrate process engineering principles with business logic
• Architect agentic systems that combine intent‑driven decision‑making, dynamic authorization, and controlled execution
• Accelerate AI adoption across the organization by democratizing access to AI capabilities, empowering business units and engineering teams to build, deploy, and operationalize intelligent workflows without deep AI expertise
• Mentor the engineering team in AI solution design patterns, governance frameworks, and best practices
• Shape the AI platform roadmap based on customer needs, operational requirements, and emerging patterns
• Collaborate with stakeholders to define AI governance, compliance, and risk controls for enterprise deployments
• Build and operationalize reusable, composable skills, orchestrations, and patterns that amplify team velocity and reduce time‑to‑value for downstream adopters

This role demands an engineer who understands both the technical depth of AI systems and the business context they operate within—and who is committed to scaling AI impact across the enterprise.

What YOU'll have

Required Qualifications & Mindset

Core Motivation & Approach

• Driven to transform enterprise operations through AI agents and intelligent automation
• Passionate about democratizing AI‑making advanced capabilities accessible to business units and non-expert engineering teams
• Motivated by solving complex, real‑world process problems with scalable, resilient solutions
• "Can-do" attitude; comfortable designing and shipping solutions under pressure and ambiguity

Technical Foundation

• Strong grasp of cloud platforms and hybrid environments; comfortable architecting for Azure, AWS, or GCP
• Deep understanding of distributed systems, microservices architecture, and cloud‑native patterns
• Proven experience with high‑level programming languages (Python preferred; Java/C# acceptable)
• Strong fundamentals: OS concepts, storage solutions, networking, and infrastructure principles

AI/LLM & Agentic Systems

• Proven track record building production LLM applications and agentic systems
• Deep expertise designing and orchestrating AI agents that make decisions, take actions, and execute workflows autonomously
• Proficiency in Python; strong experience with AI frameworks and SDKs (LangChain, LlamaIndex, OpenAI SDK, Anthropic SDK, or equivalent)
• Understanding of intent‑driven decision‑making, dynamic authorization models, and controlled execution patterns
• Experience building reusable, composable AI components (skills, orchestrations, plugins) that democratize AI across teams

Process Engineering & Business Translation

• Ability to translate business processes and operational workflows into AI‑solvable use cases
• Skilled at decomposing complex workflows into orchestrations, skills, and plugins that work together
• Comfort with process automation platforms, workflow engines, and integration patterns
• Experience collaborating with business stakeholders to identify automation opportunities and design intelligent workflows

API, Integration & Architecture

• Expert in designing and consuming APIs; strong background with async patterns and event‑driven architectures
• Experience designing scalable integration patterns that connect AI solutions to enterprise systems
• Comfortable with hybrid and multi‑cloud integration challenges

Testing, Quality & Governance

• Strong background in testing AI/ML systems (unit, integration, evaluation); familiar with model benchmarking and validation frameworks
• Deep experience designing AI governance frameworks, policy enforcement layers, and risk classification models
• Skilled at building audit trails, compliance controls, and observability for regulated industries
• Committed to quality; driven to continuous