Senior Python Full Stack Engineer (6 Yrs - Python, Azure/AWS, LLM)

Basic Function

Wolters Kluwer is looking for a hands-on Lead Enterprise Cloud Software Developer in our Engineering Team to design, build, and integrate our next generation of enterprise cloud services. Leading and mentoring our Engineering team and collaborating closely with our customers, Design and Domain Architects, Cloud Operations, Security, Compliance, and other key stakeholders, the candidate will be responsible for driving key projects and initiatives in GBS. Under moderate supervision, designs, develops, tests, debugs, and implements moderately complex software tools and utilities required for the operation, maintenance, and control of computer systems. Makes moderately complex modifications to existing software to fit specialized needs and configurations and maintains program libraries and technical documentation. Assists in planning, scheduling, and implementation. Initiates corrective action to stay on schedule.

Our Engineering team primarily focuses on designing and developing enterprise cloud services that automate traditional IT Operations tasks at scale using industry standards like infrastructure orchestration tools (such as Terraform), configuration management tools (like Ansible), Cloud software development kits (SDKs). Besides, the Engineering team is engaged in initiatives of transforming the IT Operations Services suite to be scalable and API-capable.

Our Lead Enterprise Cloud Software Developer will work closely with other Engineers leveraging a standard set of enterprise-wide artifacts such as Design Patterns and Standards, follow and establish guiding design principles ensuring the develop solutions or technical components deliver GBS strategic intent, while meeting the solution requirements providing business value.

What You'll Do

Full-Stack Engineering (Python-first): Design and implement resilient services, APIs, and UIs with Python (FastAPI/Django/Flask) and modern front-end stacks (e.g., TypeScript/React) where needed; enforce clean architecture, SOLID principles, and comprehensive unit/integration tests. Cloud Programmability: Build automation and platform capabilities using Azure and AWS SDKs (e.g., azure-sdk-for-python, boto3), event-driven designs, serverless functions, and service APIs to standardize and accelerate cloud operations. AI for Developers: use AI assistants for code and test generation, defect pattern analysis, code optimization, and documentation; Integrate LLM-powered features safely; apply prompt engineering and evaluation; follow MLOps basics for model usage in applications. Infrastructure as Code & DevOps: Author Terraform modules and CI/CD pipelines (Azure DevOps/GitLab) to deliver hands-free deployments, policy-as-code, and repeatable environments. Performance, Scalability, and Reliability: Profile and optimize code paths; apply caching, asynchronous I/O, connection pooling, efficient data models, and resource tuning; design for horizontal scale and graceful degradation; instrument services with APM/observability. Secure SDLC and Compliance: Practice threat modeling, secure coding, secret management, dependency hygiene, and code reviews; align with security champions and audit requirements. Quality Engineering: Define DoR/DoD, implement automated tests (unit, integration, performance, security), and continuously improve engineering practices. Architecture & Patterns: Apply industry-standard patterns (e.g., hexagonal architecture, CQRS where appropriate, pub/sub, idempotency) for reusability and maintainability; contribute to and consume enterprise design standards. Data & APIs: Design contract-first REST/GraphQL APIs; model relational and NoSQL data for correctness and performance; implement pagination, filtering, and rate-limiting. Collaboration & Documentation: Produce technical specifications, C4 model diagrams for C1–C3, and knowledge-base content; communicate status, risks, and trade-offs to stakeholders. Craft a culture of execution excellence coupled with innovation by incorporating best of the breed toolset Partner closely with Architecture and Engineering, Cloud Operations and Security teams to ensure the operationalization and adoption of engineering work. Mentor team members to adopt lateral thinking and “let me see how we can fix it” attitude. Guide fellow engineers and drive projects to completion by clarifying requirements, providing technical insights, and removing roadblocks. Report to stakeholders and leadership teams on the progress of key initiatives regularly Relentlessly document your implementation, patterns, practices, and processes. Breakdown: 40% Software Development Develop, debug, and document enterprise grade applications & services using Azure and AWS SDKs, leveraging GenAI code assistants for authoring, validating, optimizing code Develop, Enhance, reverse engineer, and debug new/existing Infrastructure-as-Code (IaC) capabilities leveraging tools such as Terraform, Ansible, etc. Explore new technologies, development patterns, and partake in pilots/POC/technology evaluations Participate in all aspects of the software development life cycle from design, delivery to on-going critical support Work to continually improve product functionality and quality Develop architecture, engineering and operational standards Deploy emergency bug fixes on services in production as required 30% Leadership Serve as a mentor to software developers and grow technical skills and practices for high-quality software development Lead team members in solving complex technical problems and using sophisticated analytical thought to exercise judgement and identify innovative solutions Work independently, with moderate guidance in only the most complex situations and leading teams or projects with moderate resource requirements, risk, and/or complexity 20% Software Design/Troubleshooting Contribute to software design and architecture Coordinate and assist in complex troubleshooting Performing peer reviews 10% New Technologies Actively explore new trends and identifying new ways of solving old problems, leveraging GenAI solutions approved by WK AI COE.

What You Bring To The Team

Passion and Energy to work in a team to turn a vision into a reality Empower the team to understand and be comfortable with failing fast and learning from failures to fully realize and maximize innovative spirit of the team. Establish decisive decision making utilizing strategic thinking and guidance from stakeholders and teams utilizing and supporting services. Establish strong focus on ensuring services can be effectively ran by operations. Customer-focused mindset – Drive the team to work together to solve real problems for our customers and users. A strong focus on the details, by coaching and influencing the team to pay attention to the details. Have an eye for how to market the services properly and effectively to our customers and other key stakeholders. Bring focus on identifying, building, and effectively tracking efficiencies, via metrics, for enterprise services.

Other Duties Performs other duties as assigned by management Job Qualifications & EXPERIENCE Education: Bachelor's degree in Computer Science, Information Systems, or a related field or equivalent experience Required: Advanced/Professional Technical Certificate in Azure, AWS or Kubernetes Experience: Minimum 6 years of experience in enterprise software development and cloud development: Experience with FastAPI/Django, React/TypeScript, and GraphQL. Knowledge of event-driven architectures (e.g., SNS/SQS, Azure Service Bus), streaming (Kafka/Kinesis), and pub/sub patterns. Familiarity with APM tools and SLO/SLA design; capacity and performance testing at scale. Exposure to AI/ML services (e.g., Azure OpenAI) and safe LLM integration patterns. Contributions to shared Terraform modules and internal design standards. Experience with automated deployments utilizing continuous integration and continuous delivery (CI/CD) tools (such as Azure DevOps, GitLab, GitHub, Jenkins or other well-known tools) Experience with release management, product rollouts, and service operationalization Solid and proven experience with design patterns, SOLID Principles, especially cloud resiliency patterns, working in an agile environment with an SDLC like Scrum, SaFE, etc. Being able to write scalable production-grade code leveraging Cloud software development kit (SDKs) and Cloud APIs in (at least) one of the following programming languages: Python, Java, NodeJS or Ruby

Advanced Technology Adoption and Utilization: AI Tool Proficiency: Evaluate and optimize AI tool usage for team efficiency and productivity AI Output Validation: Establish validation standards and review processes for AI-generated code Responsible AI Usage: Lead responsible AI initiatives and establish team best practices Agentic Workflow Design: Design and optimize AI agent workflows for team efficiency

Having a wide range of experiences and advanced technical acumen serving as an advisor to management Communicating difficult concepts and influencing others to adopt a different point of view Enthusiasm for staying abreast of industry trends and a keen eye for product improvements

Soft Skills: Team working A logical approach to work The ability to prioritize tasks/organize work Excellent oral, written and interpersonal English communication skills including strong presentation skills. Availability to work on extra time Problem-solving skills Patience Meticulous attention to details

Travel REquirements Position requires occasional travel on a domestic and international travel

Physical Demands Normal professional office environment: Hybrid : In-person with Wolters Kluwer colleagues at least 8 days per month

The above statements are intended to describe the general nature and level of work being performed by most people assigned to this job.  They’re not intended to be an exhaustive list of all duties and responsibilities and requirements.   Our Interview Practices To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.