Senior Software Engineer

Hillwood•Dallas, TX

About The Position

Hillwood is seeking a Senior Software Engineer for its in-house IT team in Dallas, Texas. The role combines full-stack software engineering with business engagement and delivery ownership. The engineer will work closely with business teams to identify valuable workflows, translate ambiguous needs into prioritized solutions, and own delivery from discovery through adoption and ongoing improvement. The work centers on Hillwood’s internal Core Platform, where AI tools such as Claude Code are used throughout the software development lifecycle, in collaboration with Application Development, Enterprise Data Lakehouse (EDL), and AI teams. The engineer will build and operate applications using Node.js, TypeScript, and SQL, and develop agentic applications that use LLM APIs, agent frameworks, MCP servers, and integrations with enterprise systems and data. The role also maintains and evolves shared architectural frameworks and reusable components, and applies enterprise-grade engineering practices including automated testing, code review, CI/CD, infrastructure as code, and secure development on Microsoft Azure. Success means delivering reliable, high-quality applications that users adopt and that produce measurable business outcomes.

Requirements

Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.
Six or more years of professional software engineering experience, including independently leading technical delivery of production business applications.
Demonstrated experience building full-stack applications with modern languages, frameworks, and technologies.
Experience partnering directly with business stakeholders and owning solutions from discovery and requirements through development, deployment, adoption, and ongoing operation.
Experience building on, maintaining, or extending a shared application platform or architectural framework used across multiple applications or teams.
Hands-on experience developing agentic applications using LLM APIs and agent frameworks, including tool calling, orchestration, and agent behavior evaluation.
Experience implementing Model Context Protocol (MCP) or comparable integrations connecting LLMs with enterprise applications and data.
Experience with knowledge graphs, including modeling entities and relationships and applying connected data to application or AI use cases.
Hands-on experience deploying and operating applications in Microsoft Azure.
Experience designing, maintaining, and improving CI/CD pipelines, such as GitHub Actions or Azure DevOps, for automated build, testing, and deployment.
Exceptional business-facing communication, active listening, and relationship-building skills; ability to lead discovery conversations, demonstrate solutions, and explain technical concepts to nontechnical audiences.
Strong business judgment and ownership, including the ability to identify high-value opportunities, prioritize competing needs, challenge assumptions constructively, and remain accountable for adoption and outcomes.
Ability to translate ambiguous business needs and workflows into technical requirements, solution designs, prioritized development plans, and measurable success criteria.
Strong full-stack engineering ability to design and develop secure, maintainable production applications across interfaces, backend services, APIs, integrations, and data layers.
Strong understanding of application architecture and design, including REST APIs, event-driven architectures, reliable messaging, error handling, scalability, and reusable patterns.
Proficiency with agentic application development concepts, including LLM APIs, agent frameworks, tool calling, orchestration, evaluation, and enterprise safeguards.
Proficiency with AI-assisted development tools such as Claude Code and disciplined practices for context management, task planning, review, testing, and validation.
Working knowledge of MCP and enterprise tool integration patterns connecting LLMs with applications and data.
Strong knowledge of Azure application services and cloud development concepts, including hosting, identity and access management, monitoring, and secrets management.
Strong software engineering fundamentals, including Git, automated testing, peer code review, CI/CD, infrastructure as code, and secure development.
Ability to work independently through ambiguity, adapt to unfamiliar technologies, troubleshoot across application and integration boundaries, and balance development with operational support.
Ability to make sound technical and architectural decisions while balancing immediate business needs with scalability, reusability, security, and maintainability.

Nice To Haves

Experience in forward-deployed engineering, solutions engineering, or technical consulting.
Experience integrating enterprise platforms such as ServiceNow, Box, DocuSign, or CRM systems, and middleware or integration technologies such as Boomi or Azure Logic Apps.
Experience with Databricks or another modern data lakehouse platform.
Experience in real estate, energy, investment management, or similarly complex business environments.

Responsibilities

Partner directly with business stakeholders to understand workflows, uncover pain points, and identify high-value opportunities for custom applications and agentic solutions.
Translate business needs into requirements, prioritized backlogs, and measurable success criteria; communicate tradeoffs in scope, cost, risk, and delivery time.
Determine whether business problems call for a custom application, an extension to an existing platform, or simpler automation.
Train and support users, gather feedback, and measure adoption, time savings, and business outcomes to guide improvements.
Own the software development lifecycle from discovery and prototyping through design, development, testing, deployment, production support, and enhancement.
Design and build Core Platform applications using Node.js, TypeScript, and SQL, including user interfaces, backend services, REST APIs, and event-driven integrations.
Develop agentic applications using LLM APIs, agent frameworks, MCP servers, and tool integrations with enterprise systems and EDL data.
Use AI coding tools such as Claude Code throughout the development lifecycle, applying context management, task planning, code review, and testing to validate AI-generated work.
Make architectural decisions and maintain shared frameworks, patterns, and reusable components aligned with enterprise standards and long-term business needs.
Apply automated testing, peer code review, CI/CD, infrastructure as code, and secure development practices on Microsoft Azure.
Build, maintain, and improve CI/CD pipelines for frequent, reliable, repeatable releases.
Build safeguards into agentic workflows, including access controls, human approvals, evaluations, logging, and failure handling.
Own solution reliability and performance; investigate issues, identify root causes, and implement fixes and enhancements.
Monitor application health, performance, AI solution quality, and operating costs, and use findings to improve reliability, efficiency, and user experience.
Document application architecture, technical standards, and operational procedures.
Collaborate with Application Development, EDL, and AI teams to deliver integrated solutions and promote consistent engineering practices.
Mentor engineers and contribute reusable components, architectural patterns, and development practices.
Share lessons from business engagements and delivered solutions to improve the Core Platform and accelerate future development.