Principal Enterprise Software Engineer

Wolters Kluwer

. Translate business processes and operational workflows into AI use cases solved via agents, orchestrations, skills, and plugins .

Posted 10/30/2026full-timeUnited StatesLead💰 $133,400 - $238,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and delivering AI solutions, integrating process engineering with business logic, and ensuring compliance with regulatory standards. Proficient in developing reusable AI components and frameworks while mentoring teams in best practices and governance.

Highest-signal resume keywords

AI Solution ArchitectureCloud Platforms (Azure, AWS, GCP)Python ProgrammingAI Governance FrameworksProduction LLM Applications

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Applicant Tracking System Keywords

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Hard Skills

AI Use Case TranslationDistributed SystemsMicroservices ArchitectureIntent-Driven Decision-MakingAPI Design and ConsumptionProcess AutomationTesting AI/ML SystemsData GovernanceKnowledge ManagementModel Benchmarking

Soft Skills

Cross-Functional CollaborationThought LeadershipMentoring

Tools & Technologies

LangChainLlamaIndexOpenAI SDKAnthropic SDKWorkflow EnginesEvent-Driven ArchitecturesCloud Services

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Computer Science or Related FieldPhD in Computer Science or Related Discipline

Industry Keywords

AI GovernanceCompliance ControlsRisk Classification ModelsNIST AI RMFISO/IEC 42001SOC 2ISO 27001HIPAA

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaMicroservicesPython

About the role

Key responsibilities & impact

Translate business processes and operational workflows into AI use cases solved via agents, orchestrations, skills, and plugins
Lead the design and delivery of end-to-end AI solutions integrating process engineering principles with business logic
Architect agentic systems combining intent-driven decision-making, dynamic authorization, and controlled execution
Accelerate enterprise AI adoption by democratizing access to AI capabilities
Mentor engineering teams in AI solution design patterns, governance frameworks, and best practices
Shape the AI platform roadmap based on customer needs, operational requirements, and emerging patterns
Define AI governance, compliance, and risk controls for enterprise deployments
Build and operationalize reusable, composable skills, orchestrations, and patterns
Design and execute a strategic roadmap for scaling AI adoption from pilots to production
Create reusable patterns, reference architectures, maturity models, workshops, labs, playbooks, templates, and reference implementations
Research and implement emerging AI technologies, conduct POCs, and evaluate LLM models, frameworks, and cloud services
Produce engineering design artifacts and specifications translating business workflows into agentic solutions
Implement AI safety patterns including output validation, escalation gates, controlled execution, and rollback mechanisms
Design governance frameworks aligned with NIST AI RMF and ISO/IEC 42001
Ensure compliance with SOC 2, ISO 27001, HIPAA, and other regulatory requirements
Architect and deliver multi-agent orchestration systems, tool use, long-running workflows, and intent-driven decision-making
Optimize production LLM applications for cost and performance
Participate in strategic planning and contribute to the AI platform roadmap
Pilot technologies, validate cloud provider solutions, and propose innovations

Requirements

What you’ll need

Bachelor's degree in Computer Science, Information Systems, or a related technical field (required)
Master's degree in Computer Science, Engineering, Business Administration, or related field (strongly preferred)
PhD in Computer Science, Machine Learning, or related discipline (a plus)
Strong grasp of cloud platforms and hybrid environments; 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
Proven track record building production LLM applications and agentic systems
Proficiency in Python and experience with AI frameworks and SDKs such as LangChain, LlamaIndex, OpenAI SDK, or Anthropic SDK
Understanding of intent-driven decision-making, dynamic authorization models, and controlled execution patterns
Experience building reusable, composable AI components, including skills, orchestrations, and plugins
Ability to translate business processes and operational workflows into AI-solvable use cases
Experience with process automation platforms, workflow engines, and integration patterns
Expert in designing and consuming APIs; strong background with async patterns and event-driven architectures
Strong background in testing AI/ML systems, model benchmarking, and validation frameworks
Experience designing AI governance frameworks, policy enforcement layers, risk classification models, audit trails, compliance controls, and observability
Deep experience with Azure services or equivalent AWS/GCP services
Understanding of data pipelines, vector databases, and knowledge graph construction
Experience designing data governance and knowledge management for AI systems
Cross-functional collaboration with business stakeholders, customers, security, and compliance teams
Thought leadership in AI solution architecture, governance, and best practices

Benefits

Comp & perks

Bonus eligibility
Medical, Dental, & Vision Plans
401(k)
FSA/HSA
Commuter Benefits
Tuition Assistance Plan
Vacation and Sick Time
Paid Parental Leave