Senior technical leader responsible for defining the end‑to‑end architecture of enterprise data platforms, advanced analytics solutions, and AI/ML capabilities.
Compensation
The salary range for this role is 132,400 USD - 251,600 USD.
Responsibilities
Define the long‑term architecture for data, analytics, and AI/ML platforms in alignment with enterprise digital strategy.
Develop reference architectures, design patterns, and platform standards for cloud, Lakehouse, and AI ecosystems.
Define and lead technology proof of concepts to ensure feasibility of architecture solutions.
Provide strong thought leadership in pursuit of modern architecture principles and technology modernization.
Evaluate emerging technologies and provide strategic recommendations (AI, knowledge graphs, real‑time streaming, ML Ops, etc.).
Requirements
Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
Client-facing Enterprise Data Architects helping clients transform fragmented data estates into AI-ready foundations, advising on architecture decisions across cloud data platforms, lakehouse/warehouse patterns, and GenAI retrieval.
Responsibilities
Help clients transform fragmented data estates into AI-ready foundations
Advise on architecture decisions across cloud data platforms, lakehouse and warehouse patterns, data products, semantic layers, metadata, lineage, governance, knowledge graphs and GenAI retrieval patterns
Diagnose ambiguous client problems, shape options, make trade-offs explicit, and translate complex data architecture issues into clear decisions
Work in cross-functional teams alongside product owners, data scientists, ML and GenAI engineers, data engineers, business analysts and client stakeholders
Produce target-state architectures, maturity assessments, platform option appraisals, data product designs, governance models, lineage maps, ontology and semantic models, integration patterns, GenAI data-readiness assessments and implementation roadmaps
Lead global knowledge operations and AI evaluation, building and operating a worldwide knowledge management system and AI-enabled knowledge services.
Responsibilities
Establish and run a global knowledge operations framework
Design and implement global operating mechanisms for knowledge production, governance, release, consumption, feedback, repair, regression and retirement
Define responsibilities and escalation paths between Platform, Channel, Geo, AI Engineering, Evaluation and external vendors
Create a unified service catalog, priority rules, SLA, operating rhythm and management dashboard
Drive cross‑regional standardization while preserving necessary local differences
Lead business architecture for Agentic AI transformation in global private banking.
Compensation
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.
Responsibilities
Define and articulate target-state business architecture for AI-enabled wealth management
Drive large-scale functional solutions across multiple lines of business
Partner with senior stakeholders globally to gather requirements
Synthesize business and functional requirements into technology-based solutions
Identify and prioritize high-impact AI use cases
Requirements
Formal training or certification on software engineering concepts
Nice to have: leadership in AI-driven transformation programs
Design, develop, and evolve autonomous operation agents for mining sites, integrating large language models, retrieval-augmented generation, and workflow orchestration.
Responsibilities
Plan and evolve application technology for autonomous operation agents
Design and develop professional agents for various user roles and business scenarios
Build agent scenario understanding, business reasoning, task decomposition, and multi-step execution
Convert existing autonomous operation system capabilities into callable professional tools and services
Develop cross-system and cross-domain agent workflows
Requirements
Master's degree in Computer Science, Artificial Intelligence, Software Engineering, Automation, Data Science or related field
As a deployment engineer at WRITER, you'll be at the forefront of expanding human capacity through superintelligence. You'll partner directly with our leading enterprise customers, uncovering their unique business challenges and architecting AI-powered solutions that leverage our powerful platform and enterprise-grade LLMs.
As a deployment engineer at WRITER, you'll partner with leading enterprise customers to architect AI-powered solutions leveraging the platform and enterprise-grade LLMs.
Locations (6)
Chicago, Illinois, United States
San Francisco, California, United States
Austin, Texas, United States
New York City, New York, United States
Seattle, Washington, United States
Consultant Data Gouvernance & Data Modelisation (H/F)
Design and develop LLM- and RAG-based solutions to automate SW-FMEA generation from software architectures, SysML specifications, and safety documentation.
Responsibilities
Design and develop LLM- and RAG-based solutions to automate SW-FMEA generation from software architectures, SysML specifications, and safety documentation.
Develop automated C/C++ code inspection tools using LLMs and AST parsers to identify failure prevention and detection mechanisms.
Ensure traceability between SW-FMEA analyses and safety mechanisms identified in source code.
Implement automated CI/CD pipeline checks to detect code changes that could compromise critical safety mechanisms.
Integrate analysis outputs with requirements management and ALM tools, including Jira, Jama, and Polarion.
Incubate and validate new growth opportunities at the intersection of AI, data, product, and pharma and biotech customers across R&D and commercial functions.
Responsibilities
Own intake and shaping of strategic enterprise opportunities that require new capabilities, integrations, packaging, or market positioning.
Drive executive decisioning on whether to pursue, park, or decline opportunities with clear rationale, options, and business and technical implications.
Lead senior R&D and commercial conversations and translate demand into scalable solution paths.
Ground discovery in customers’ end-to-end workflows and decision points to define target state, success criteria, and constraints.
Translate ambiguous asks into a solution concept and delivery path.
Requirements
advanced degree in life sciences, engineering, or a related field
Competitive compensation, company stock options and 401k
Responsibilities
Partner deeply with enterprise customers to identify strategic AI use cases, validating technical feasibility and owning the end-to-end implementation of tailored solutions
Architect and deliver custom applications, templates, and integrations leveraging WRITER's platform, APIs, and Knowledge Graph capabilities to solve complex business challenges
Translate intricate technical concepts and platform capabilities into clear, prescriptive solution recommendations, guiding customers through the generative AI landscape
Collaborate relentlessly with internal Product and Engineering teams, providing crucial customer feedback that directly influences our product roadmap and drives continuous innovation
Drive down customer time-to-value by developing scalable processes, robust documentation, and efficient workflows for technical integrations
Requirements
Nice to have: prompt design
Nice to have: linguistic principles for AI applications
Competitive compensation, company stock options and 401k
Responsibilities
Partner deeply with enterprise customers to identify strategic AI use cases, validating technical feasibility and owning the end-to-end implementation of tailored solutions
Architect and deliver custom applications, templates, and integrations leveraging WRITER's platform, APIs, and Knowledge Graph capabilities to solve complex business challenges
Translate intricate technical concepts and platform capabilities into clear, prescriptive solution recommendations, guiding customers through the generative AI landscape
Collaborate relentlessly with internal Product and Engineering teams, providing crucial customer feedback that directly influences our product roadmap and drives continuous innovation
Drive down customer time-to-value by developing scalable processes, robust documentation, and efficient workflows for technical integrations
Requirements
Nice to have: Prompt design
Nice to have: Linguistic principles for AI applications
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