Lead Product Software Engineer

Wolters Kluwer•Coppell, TX

1d•$116,400 - $204,100

About The Position

As Technical Lead, you will shape the technical direction of a multi-year transformation of Business License’s mature product portfolio into a scalable, cloud-based ecosystem. You will partner with Product and Engineering management and own delivery across customer self-service, License Intelligence, workflow, reporting, integrations, and AI-enabled compliance experiences. The role combines hands-on engineering with technical leadership, architecture, delivery planning, and mentoring. You will guide modernization toward modular business capabilities, modern APIs and services, and cloud-based operations. You will also help establish responsible practices for AI-assisted and agentic development, including validation of AI-generated code and design of agentic workflows. The role includes ownership of application and AI-service health, participation in planned deployments and incident response, and occasional urgent production fixes outside normal hours when needed.

Requirements

8+ years of software engineering experience with deep .NET and Angular expertise.
At least 1 year of agentic AI development experience.
Proven technical leadership in architecture, design reviews, roadmap planning, and cross-team delivery.
Strong skills in REST API design, SQL Server, relational design, IIS and self-hosted deployments, Azure, Azure DevOps CI/CD, and GitHub.
Strong testing discipline, including NUnit, Jasmine, and code coverage, plus production support experience.
Advanced AI tool proficiency, including responsible-AI practices and validation of AI outputs.
Excellent communication, analytical, and problem-solving skills, with strong ownership and accountability.
Agile/Scrum experience.

Nice To Haves

Python or a similar scripting language for AI/agent development.
LLM architecture knowledge, including inference, context limits, and cost/latency tradeoffs.
Experience with ReAct, Chain-of-Thought, and structured-output prompting.
Experience with agentic RAG, vector databases, and embeddings.
Experience with LangChain, AutoGen, CrewAI, and multi-agent orchestration.
Knowledge of agent ecosystem design, including reasoning engines, memory, tool interfaces, and goal management.
Experience with model evaluation, hallucination mitigation, and safe action loops.
TensorFlow/PyTorch and reinforcement learning concepts.
Legacy modernization experience, such as Silverlight/Web Forms to Angular.
OAuth/OIDC and Oracle experience.

Responsibilities

Partner with product and engineering management to define technical strategy and roadmap, translating business priorities and customer needs into technical priorities.
Own delivery from requirement clarification and design through implementation, testing, release, and post-release validation.
Create delivery plans covering architecture, milestones, sequencing, owners, dependencies, timelines, and success measures.
Manage competing priorities across workstreams by proposing options, sequencing work, and assigning ownership.
Lead architecture and design reviews, document major decisions, and balance delivery, reliability, security, quality, maintainability, and cost tradeoffs.
Guide modernization from tightly coupled legacy applications toward modular business capabilities, modern APIs and services, and cloud-based operations.
Identify risks, blockers, and dependencies early; communicate scope or timeline changes, recommend mitigations, and escalate when needed.
Represent the team in cross-team technical discussions and drive decisions and dependencies to resolution.
Own the technical and operational health of the team's applications and AI services; monitor service health with New Relic and Datadog, and maintain prioritized plans for technical debt, reliability, and architecture improvements.
Establish team practices for planning, testing, release readiness, quality standards, incident follow-up, and continuous improvement.
Evaluate and optimize AI tool use, establish validation standards and review processes for AI-generated code, and lead responsible-AI practices.
Design and optimize agentic workflows for team efficiency and product features.
Remain hands-on with .NET, Angular (v18+/NgRx), REST APIs, SQL Server, and Azure.
Mentor engineers through delegation and actionable feedback, and provide management with evidence-based input on growth and performance.
Participate in planned deployments, incident response, and urgent production fixes outside normal hours when needed.