Staff Software Engineer

Newmark•Dallas, TX

21d•Hybrid

About The Position

This role involves owning and driving the technical architecture for complex, cross-team full-stack initiatives. The engineer will design, build, and maintain scalable, high-performance web applications and distributed services in a cloud-native environment. A key focus will be architecting and integrating agentic AI workflows, including autonomous agents, LLM-driven automation, and AI copilots, into engineering and product systems. The position also entails setting engineering standards, leading technical design reviews, partnering with leadership to translate business strategy into technical roadmaps, and identifying/resolving systemic issues. Mentoring senior and mid-level engineers in both full-stack and AI engineering practices, and driving the adoption of modern technologies are also core responsibilities. The role requires staying aware of emerging technologies, particularly in agentic AI and automation.

Requirements

Bachelor's degree in Computer Science, Engineering, MIS, or related field preferred.
12+ years of experience in software engineering, with demonstrated experience architecting full-stack web applications at scale.
Expert-level proficiency in modern JavaScript/TypeScript frameworks (e.g., React, Next.js) and backend languages (e.g., C#, Node.js, Java, or similar).
Deep understanding of distributed systems design, microservices architecture, and API design (REST/GraphQL).
Strong experience with cloud platforms (Azure, AWS, or GCP) and cloud-native architecture patterns.
Hands-on experience building or integrating agentic AI systems, LLM-powered applications, or AI agent orchestration frameworks (e.g., LangChain, AutoGen, Semantic Kernel, MCP).
Proven track record of leading large-scale technical initiatives across multiple teams.
Strong background in database design, including both relational (SQL) and NoSQL data stores.
Deep understanding of CI/CD pipelines, infrastructure as code, and DevOps practices.
Demonstrated ability to mentor engineers and influence technical direction without direct reporting authority.

Nice To Haves

Experience designing multi-agent systems, tool-calling architectures, or retrieval augmented generation (RAG) pipelines.
Experience with event-driven architectures and real-time data processing (e.g., Kafka, Event Hubs, Kinesis).
Familiarity with containerization and orchestration technologies (Docker, Kubernetes).
Prior experience in commercial real estate, fintech, or operations/transaction systems.
Track record of speaking, writing, or open-source contributions that demonstrate technical thought leadership, especially in applied AI.

Responsibilities

Own and drive the technical architecture for complex, cross-team full-stack initiatives spanning front-end, backend, and data layers.
Design, build, and maintain scalable, high-performance web applications and distributed services in a cloud-native environment.
Architect and integrate agentic AI workflows (autonomous agents, LLM-driven automation, AI copilots) into engineering and product systems to drive efficiency and new capabilities.
Set engineering standards and best practices for code quality, system design, testing, and deployment across the organization, including responsible use of AI-assisted development tools.
Lead technical design reviews and provide architectural guidance to multiple engineering teams.
Partner with product, design, and engineering leadership to translate business strategy into scalable technical roadmaps, including AI-driven product capabilities.
Identify and resolve systemic performance, reliability, and scalability issues across the stack.
Mentor and coach senior and mid-level engineers, raising the technical bar across the organization on both full-stack and AI engineering practices.
Drive adoption of modern frameworks, tools, and engineering practices, including agentic AI and LLM tooling, to improve developer velocity and system resilience.
Maintain awareness of emerging technologies and industry trends, particularly in agentic AI and automation, and assess their applicability to the business.