Role Description Own the roadmap for Smartech AI's platform layer — the analytics, models, and shared services (anomaly detection, prediction, contextualization) that turn real-time plant data into reusable capabilities. Deliver well-governed services that accelerate every operator- and operations-facing application across the portfolio. Key Responsibilities - Platform Strategy & Roadmap: Own the roadmap for models, inference APIs, and shared services built on real-time plant data; prioritize capabilities that unlock application value. - Adoption & Enablement: Drive adoption through SDKs, documentation, and enablement; gather requirements from application teams and plant stakeholders. - Execution & Delivery: Lead delivery with ML and engineering in Agile/Scrum — owning the backlog, story writing, and sprint planning. - Responsible AI & Governance: Embed evaluation, monitoring, and model governance for plant-critical use; ensure data privacy and compliance. Key Performance Indicators - Adoption: Apps / teams using services, API & SDK usage. - Performance: Service uptime / latency (SLOs), model accuracy on plant data. - Delivery: Sprint commitments met, concept-to-GA time. Qualifications - 5+ years in software product management / product ownership, including 2+ years owning a technical or platform product in an Agile/Scrum environment — backlog ownership, story writing, and sprint planning with engineering. - 2+ years in industrial / manufacturing software — Industrial IoT, MES, SCADA / historian, or plant-operations SaaS — with a demonstrated understanding of real-time plant data and operator-facing systems. - Proven record shipping operator- or operations-facing applications — dashboards, alerting, visualization, or workflow tools built on live / streaming data. Knowledge, Skills & Abilities - AI/ML Fluency: Model lifecycle, inference, and APIs on plant data. - Platform PM: Ships developer- and application-facing services. - Industrial Domain: Understands real-time plant data and use cases. - Agile Ownership: Backlog, stories, and sprint planning with engineering. - Responsible AI: Evaluation, monitoring, and model governance. - Influence: Effective across engineering, data, and application teams. Other We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law. To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

Role Description We're looking for an experienced, innovative AI Engineer to push the boundaries of LLM technology and build intelligent features for our enterprise platform. Pairing strong Python and cloud backend skills with hands-on generative AI experience (LLMs, prompt engineering, RAG, and agents), you'll design and deploy AI-driven solutions from prototype to production - helping define a new class of engineering role that blends robust system design with state-of-the-art AI. What You'll Do - Design & ship AI features: Lead the design, development, and deployment of generative AI and LLM-powered services — intelligent chatbots, AI-driven recommendations, workflow automation - that deliver engaging, human-centric experiences. - Build RAG pipelines: Design, implement, and continuously optimize end-to-end RAG pipelines (data ingestion and parsing, chunking, vector indexing, prompt engineering) so our systems retrieve and use knowledge accurately. - Build LLM agents: Develop and refine LLM-based agentic systems for complex, multi-step tasks - incorporating planning, memory, and tool use, and applying emerging best practices to make agents more reliable. - Evaluate & iterate: Rigorously evaluate models and pipelines on accuracy, latency, and hallucination rate, using thorough testing and user feedback to improve prompts, parameters, and data processing. - Engineer for production: Write clean, maintainable, testable code with strong monitoring and logging, ensuring AI components are scalable and fit the overall system architecture. - Collaborate & innovate: Partner with product, design, and engineering to integrate AI seamlessly into products, mentor teammates on generative AI best practices, and continuously explore new AI advancements to bring into the platform. Qualifications - 3+ years (mid-level) / 5+ years (senior) of backend engineering, with expert Python, scalable API/service design, strong system design, and experience deploying on AWS or similar cloud platforms. - Proven experience building real products on LLMs/generative AI (chatbots, semantic search, AI assistants), with hands-on RAG and agent work and a solid grasp of model behavior and failure modes. - Strong in prompt design, function calling/structured outputs, tool use, context-window management, and the RAG levers that matter (parsing/chunking, metadata, re-ranking, embedding/model selection); pragmatic model/provider trade-offs (latency, cost, context, safety); product-aligned evaluation (golden sets, prompt unit tests, offline checks, online A/Bs); and fundamentals of embeddings, tokenization, vector search, and transformers. - Hands-on with LLM orchestration libraries (LangChain, LlamaIndex) and vector databases (Pinecone, Chroma, Milvus). - Able to productionize LLM/RAG services as high-availability, low-latency backends on AWS (ECS/EKS/Lambda, API Gateway/ALB, S3, DynamoDB/Postgres, OpenSearch, SQS/SNS/Step Functions, KMS, VPC) with IaC (Terraform/CDK), strong observability, security (PII handling, encryption, least-privilege IAM), progressive delivery (blue/green, canary, feature flags), and cost/latency strategies like caching, batching, streaming, and multi-provider fallbacks. - Excellent communication to explain complex AI concepts to non-technical stakeholders, plus a self-directed, "figure it out" approach to troubleshooting across the stack and rapid prototyping in a fast-paced environment. Requirements - Enterprise B2B SaaS experience. - Full-stack/frontend depth (modern frameworks or Node.js). - Complex multi-agent or multi-modal AI. - Early-stage startup experience. - Active involvement in the AI community (open source, research, or blogging). Benefits - Top of market salary. - 49 days paid time off. - PTO, full benefits, retirement and wellness plans. - Professional development support, remote workspace setup bonus. - Annual company offsites in exciting locations around the world. Company Description - Certa was named a Leader in the inaugural 2026 Gartner Magic Quadrant for Third-Party Risk Management Tools. - We've been honored across the analyst and awards landscape, including Top Tech and Customer Value distinctions in The Hackett Group's 2026 Risk Management SolutionMap. - Certa was named one of Forbes' Best Startup Employers in the US. - We've processed over 10 million entities for 100,000+ users across 120+ countries. - We're well-funded by leading investors including Fin Capital, Vertex Ventures, and Point72 Ventures.

• Work closely with founding team to design and build management training solution • Own product surfaces end-to-end from idea through implementation • Produce high-quality software with minimal bugs • Optimize LLM usage and build supporting infrastructure • Build data integrations and use data effectively • Serve as a role model for team culture

Role Description Build the next generation of scalable, AI-powered software with modern tools, cloud-native systems, and world-class engineering practices. Cushman & Wakefield is investing heavily in modernizing and transforming its global technology platforms — and we are looking for a Sr AI Engineering Lead who wants to own technical direction end to end. AI is the primary differentiator here, not a side feature: you will define how intelligence is embedded across products built on top of a complex, multi-source enterprise data estate spanning a global commercial real estate firm. Technology Strategy & Vision - 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. Hands-On Full-Stack & Platform Engineering Leadership - Guide the design and development of solutions built with: - Frontend: React, Next.js, TypeScript, Tailwind, micro-frontends - Backend: Node.js, Python (FastAPI), Go, .NET Core, event-driven microservices - Cloud & Infra: Azure (preferred), AWS, Kubernetes (AKS/EKS), serverless architectures, Terraform - Data & AI: Databricks (Genie/AI-BI, Mosaic AI Agent Framework, Unity Catalog, Delta Lake, medallion architecture, model serving), Azure Data Lake, vector databases, LLM orchestration and agentic frameworks - APIs: GraphQL, gRPC, REST at scale - Drive innovation by embedding AI/ML, automation, production prompt engineering, intelligent workflows, and data interoperability into core products. Execution, Quality & Delivery Excellence - Champion excellence through best practices: - Enterprise-grade CI/CD (Azure DevOps, ArgoCD) - Automated testing, contract testing, and quality gates - Observability platforms (Prometheus, OpenTelemetry, Grafana, New Relic, Datadog) - Secure-by-design principles, threat modeling, zero trust patterns - Oversee engineering delivery across multiple squads — ensuring consistency, velocity, and reliability. AI Engineering Standards - 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 Architecture, Governance & Platform Integrity - 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. Stakeholder Alignment & Technical Influence - 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. Qualifications - 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. Leadership Competencies - 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. Bonus Experience (Highly Attractive) - 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, vision, and dental insurance - Flexible spending accounts - Health savings accounts - Retirement savings plans - Life and disability insurance programs - Paid and unpaid time away from work Compensation The compensation for the position is: $124,780.00 - $146,800.00. The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate’s experience and qualifications. Company Description Cushman & Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated. In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at Cushman & Wakefield, please call the ADA line at 1-888-365-5406 or email Accommodations@cushwake.com. Please refer to the job title and job location when you contact us.