Lead Product Software Engineer

Wolters Kluwer•Houston, TX

16d

About The Position

We’re looking for a Lead Product Software Engineer to drive end‑to-end solution design and delivery across our .NET and Angular stack on Microsoft Azure. You’ll set a high bar for engineering quality, guide teammates, and turn complex business needs into reliable, scalable software. If you enjoy building well‑designed systems, optimizing performance, and using AI tools responsibly to boost team velocity, this role is a great fit.

Requirements

Software Engineering: Design, build, and maintain software using engineering fundamentals and sound judgment.
Software Development (.NET, Angular, Azure): C#/.NET (ASP.NET Core), Angular/TypeScript, and Azure services to deliver secure, scalable, high‑quality applications.
Programming: Proficient in C#, TypeScript, SQL, and supportive scripting languages.
Problem Solving: Structured, data‑driven approach to understanding and resolving complex issues.
Analysis: Break down complex problems; understand interactions and dependencies across systems.
Testing: Design and implement comprehensive testing strategies; emphasize automated testing and continuous quality.
Agile: Collaborate effectively in iterative development environments; respond well to change.
Source Code Repository: Strong Git practices (branching, pull requests, code reviews) using Azure DevOps or GitHub.
Relational Database: Design, query, and optimize SQL Server/Azure SQL with strong data modeling and indexing skills.
APIs: Design, secure, document, and evolve RESTful APIs and service integrations.
Design: Communicate system architectures and software designs clearly through diagrams and documentation.
Framework: Apply modern patterns including DI, domain‑driven design concepts, and modular, cloud‑ready architectures.
Automation: Build CI/CD pipelines, promote infrastructure automation, and define quality gates.
Documentation: Produce clear, concise documentation to support design, onboarding, and long‑term system maintenance.
Kubernetes & Containerization: Package and operate services using Docker and Kubernetes, especially AKS, with strong understanding of deployment strategies and observability.
Advanced Technology Adoption and Utilization: AI Tool Evaluation and Adoption: Select and introduce AI tools where they add meaningful value. AI Output Quality: Ensure AI‑generated code is validated and reviewed with appropriate rigor. Responsible AI Usage: Define safe and compliant usage patterns aligned to internal policies. AI Development Workflow: Embed AI thoughtfully into daily development workflows.

Nice To Haves

Cloud‑Native Architecture: Microservices, 12‑factor apps, distributed systems.
CI/CD & DevOps: Automated pipelines, testing, and gated releases.
Infrastructure as Code: Bicep, Terraform, ARM for consistent provisioning.
Observability: Tracing, metrics, logs, alerting, and SLO practices.
Security: OAuth2/OIDC, secure coding, secrets management, scanning tools.
API Governance: Versioning, OpenAPI/Swagger, backward compatibility.
Messaging & Events: Azure Service Bus/Event Hubs, Kafka patterns.
Caching: Redis and in‑app caching strategies.
Front‑End Performance: Profiling, lazy loading, and Angular optimization.
Release Strategies: Canary, blue/green deployments, feature flags.
Production Readiness / SRE: Runbooks, incident response, RCA processes.
Technical Communication: Clear written documentation and cross-functional communication.

Responsibilities

Design Collaboration and Specification: Partner with product, UX, and architecture to translate business needs into clear technical designs, API contracts, and delivery plans.
Innovative Software Application Design: Lead the design and development of modern applications using C#/.NET (ASP.NET Core), Angular/TypeScript, and Azure services; choose patterns that scale and last.
Team Supervision: Mentor engineers through code reviews, pairing, and design sessions. Provide guidance on best practices, trade‑offs, and technical decisions.
Technical Requirements Documentation: Produce and maintain technical specs, architecture diagrams, and standards to keep teams aligned and efficient.
Advanced Data Analysis: Use data insights to inform software design and prioritization; validate performance assumptions with real metrics.
Performance Optimization Expertise: Profile and optimize APIs, Angular front‑ends, SQL queries, and cloud resources. Lead caching, indexing, and cost/performance optimization initiatives.
Containerization & Orchestration (Kubernetes): Design and operate containerized workloads in AKS (or similar Kubernetes environments), including resource tuning, deployment patterns, and workload observability.
Testing Strategy Development: Define and enforce testing strategies (unit, integration, contract, E2E, performance). Champion automation and continuous quality gates.
Data Preparation and Analysis: Model, query, and optimize SQL Server/Azure SQL schemas and data access patterns; ensure data correctness and resiliency.
High‑Level Technical Support: Provide advanced technical support for maintenance, usage, and issue resolution; act as an escalation point for complex challenges.
Resource Requirement Identification: Assess personnel, tooling, and infrastructure needs; communicate clear recommendations that support planning and prioritization.
Real‑Time System Monitoring: Implement proactive monitoring and alerting using Azure Monitor, Application Insights, and Kubernetes‑native observability tools.
Responsible AI & Advanced Technology Adoption: Evaluate AI development tools, establish validation standards for AI‑assisted code, and define responsible usage guidelines aligned with policy and compliance.