Staff Software Engineer

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About Us

At Newmark, we are a leading commercial real estate advisor and service provider to large institutional investors, global corporations, and other owners and occupiers. Our mission is to make it easier to lease, buy or sell properties in the retail, office, multifamily, industrial, student housing or hospitality sectors, our team is equipped to guide clients through the real estate process and more rewarding for everyone.

Building your career? Build it better at Newmark. Join us and help change the world of real estate.

Job Description

We are looking for a highly skilled Staff Software Engineer to join our team and drive the development of cutting-edge applications to drive our Occupier solutions business.

You will play a technical leadership role, influencing both strategy and execution while mentoring engineers and collaborating with cross-functional teams to build next-generation Occupier solutions, micro frontend architectures, modern React-based applications, AI-driven data platforms, and computing infrastructure that ensures high availability, security, and consistency in a fast-paced environment. This role requires deep expertise in building cloud native applications, distributed systems, cloud infrastructure, and AI/ML workloads to deliver reliable, intelligent, and high-performing platforms at scale.

Key Responsibilities

• Architect & Build

  : Architect, design, and develop scalable, fault-tolerant, and highly available applications across frontend (React, micro frontends) and backend services deployed in Azure cloud.

• AI-Driven Automation

  : Implement AI-powered workflows and experiment with emerging AI/ML capabilities that help our brokers streamline their work and improve operational efficiency.

• Security & Compliance

  : Ensure adherence to data security, privacy regulations (GDPR, CCPA, PCI-DSS), and financial compliance standards.

• Cross-Functional Leadership

  : Partner with engineering, product, risk, and compliance teams to drive innovation in transactional and AI-powered systems.

• Mentorship & Code Excellence

  : Provide technical mentorship and uphold high engineering standards through code reviews, system design discussions, and best practices.

• Technical Leadership

  : Lead and facilitate technical discussions, design reviews, and Scrum ceremonies.

• Engineering Best Practices

  : Ensure best practices across code quality, testing, observability, and deployment, including writing and maintaining strong unit test coverage.

• Influence & Challenge

  : Influence and challenge requirements and approaches with data-driven insights, ensuring scalability and maintainability.

• DevOps Thought Leadership

  : Demonstrates DevOps thought leadership by driving best practices, fostering a culture of collaboration, and continuously improving CI/CD pipelines, release automation, and observability practices.

• Architecture Review

  : Document design decisions and present them to the Architecture Review Board (ARB) for review.

• Technical Risk Management

  : Identify risks early during planning and create mitigation strategies to avoid last-minute changes.

• Technical Debt

  : Document and prioritize technical debt, ensuring it is incorporated into sprints.

• Build vs Buy:

  Exhibits strategic decision-making in Build vs Buy scenarios by evaluating technical feasibility, cost, time-to-market, and long-term scalability to align with business objectives.

Basic Qualifications

• 15+ years of experience in software engineering, distributed systems, and application development.
• Deep expertise in transactional database architectures (SQL, NoSQL, NewSQL), ACID principles, and event-driven processing.
• Technical Debt: Document and prioritize technical debt, ensuring it is incorporated into sprints.
• Strong coding skills in C#, React/TypeScript, and Python (preferred) with expertise in distributed computing, microservices, micro frontend architectures, and containerized deployments (Kubernetes, Docker).
• Strong understanding of MLOps, data pipelines (Kafka, Spark, Flink), and cloud-native AI/ML deployment (Azure preferred; AWS/GCP experience acceptable).
• Domain expertise in Commercial Real Estate (CRE) is a plus; ability to quickly learn the business domain is essential.