Note: The job is a remote job and is open to candidates in USA. Cushman & Wakefield is investing in modernizing and transforming its global technology platforms with AI-powered software and cloud-native systems. The Senior AI Engineer will define technical direction, lead full-stack and platform engineering, establish AI engineering standards, oversee delivery across multiple squads, and align technical strategies with business goals.
Responsibilities
- Define multi-year architectural direction across full-stack systems, cloud platforms, and AI-driven products — focusing on scale, resilience, security, and global performance
- Establish standards for agentic workflows, intelligent search, conversational interfaces, and data-grounded reasoning across CW's enterprise platforms
- Shape engineering roadmaps using best-in-class development stacks (e.g., TypeScript/Node.js, Python, Go, C#, React, Next.js, microservices, event-driven architectures)
- Foster a modern engineering culture emphasizing automation, craftsmanship, clean architecture, and continuous improvement
- Guide the design and development of solutions built with:
- Drive innovation by embedding AI/ML, automation, production prompt engineering (system prompt architecture, context injection, business-rule encoding, citation and grounding patterns), intelligent workflows, and data interoperability into core products
- Champion excellence through best practices:
- Oversee engineering delivery across multiple squads — ensuring consistency, velocity, and reliability
- Define and enforce AI engineering standards across products and external delivery teams:
- AI evaluation framework design — golden-question sets, hallucination measurement, regression testing, and model quality gates for production AI systems
- Pre-semantic data contracts — schema stability requirements, canonical entity ID definitions, and data quality thresholds that AI systems can depend on
- AI governance — access control patterns for confidential and client data, responsible use guardrails, and auditability requirements for AI-generated outputs
- LLM system design standards — prompt versioning, context window management, grounding and citation patterns, and failure-mode handling
- Lead architectural reviews and key design decisions across services, domains, and integrations
- Establish patterns for scalability, fault tolerance, global data compliance, and cost optimization
- Maintain high standards in coding, cloud security, API governance, and data interoperability
- Partner with Product, Architecture, Operations, and Client Technology to prioritize work, unblock teams, and drive outcomes
- Represent engineering in executive and governance forums with clarity around architectural options, tradeoffs, and investment needs
- Translate complex engineering realities into clear business insights that support strategic decision-making
Skills
- Bachelor's/Master's in Computer Science, Engineering, or related field
- 8+ years of software engineering experience and 3+ years leading technical teams or engineering managers
- Deep experience with modern full-stack development, cloud-native systems, distributed architectures, and high-scale platforms
- Demonstrated experience designing and shipping production LLM/AI systems: agentic frameworks, RAG pipelines, text-to-SQL grounding, and AI evaluation harnesses
- Hands-on expertise with Python, Go, TypeScript/JavaScript, C#, Java, SQL/NoSQL; React, Next.js, Node.js, FastAPI, .NET, Angular Core, microservices, Kubernetes
- Strong command of DevOps, CI/CD automation, infrastructure-as-code, and observability
- Strategic engineering thinker who balances innovation with disciplined execution
- Proven ability to mentor engineers, grow high-performing teams, and attract top talent
- Ability to influence product, business, and technical leadership
- Comfortable making architectural decisions that require both technical depth and business awareness
- Azure (preferred)
- Distributed event streaming (Kafka, EventHub), CQRS/event-sourcing patterns
- Experience building platforms used across global organizations
- Experience technically overseeing external development vendors or contract engineering teams
Benefits
- Health insurance
- Vision insurance
- Dental insurance
- Flexible spending accounts
- Health savings accounts
- Retirement savings plans
- Life insurance programs
- Disability insurance programs
- Paid and unpaid time away from work
- Fully Remote
Company Overview
Company H1B Sponsorship