Job Title: AI Solution Architect

Company Name: Cutsforth

Job Details: $199k-$242k/yrRemoteFull,Time

Job Url: https://hiring.cafe/viewjob/t4zvpoi7lkoj70f7

Job Description: Posted 5d agoAI Solution Architect@ CutsforthView All JobsWebsiteFerndale, Washington, United States$199k-$242k/yrRemoteFull TimeResponsibilities:Define architectures, Lead AI strategy, Collaborate stakeholdersRequirements Summary:5+ years data/AI engineering or architecture with enterprise AI/ML experience; strong in Databricks, Python, LLMs, and cloud integration.Technical Tools Mentioned:Python, SQL, Scala, Databricks, Delta Lake, Unity Catalog, Mosaic AI/Databricks AI, MLflow, Jupyter, Git, Azure, Docker, Kubernetes, LLMOps, Data Lake, Lakehouse, Cursor, Claude, Devin AI, Vector search, ETL/ELT
Role Information:Job Title: AI Solution ArchitectWork Location: Fully remote positionEmployment Type: Full-timeEmployment Status: Exempt, salariedVisa sponsorship is not available for this position.Must reside in the United States.We are not accepting applicants for remote workers in California, Illinois, and New York at this time.Compensation:$198,654 - $242,175 depending on years of experience​​​​Role Overview:The AI Solution Architect designs and leads the enterprise-wide AI strategy, translating business objectives into scalable, secure, and production-ready AI architectures. This strategic role involves defining end-to-end AI blueprints: including data pipelines, model selection, integration patterns, governance frameworks, and deployment models, while ensuring alignment with organizational goals, compliance requirements, and emerging AI technologies. The architect collaborates with stakeholders across data science, engineering, and executive teams to roadmap AI adoption, evaluate technologies, mitigate risks, and enable transformative, enterprise-grade AI capabilities that drive long-term business value. Key Responsibilities:Defines solution architectures for artificial intelligence systems, including data pipelines, feature stores, vector indices, model endpoints, orchestration, and serving layers Designs LLM-centric patterns (prompting, functional tool calling, memory, grounding, guardrails) and retrieval augmented generation workflows with appropriate evaluation strategies.  Engineers’ agentic architectures and multi agent handoffs, specific toolkits, planning/execution loops and safety boundaries for autonomous or semi-autonomous tasks. Selects and integrates cloud services for training, tuning and inference. Integrates AI services with enterprise platforms, and designs adapters, webhooks, and contract test for reliability.  Leads proof of concept pilots, validates feasibility, scales successful patterns, and hardens prototypes into production ready services. Defines reference architectures, templates, Software Development Kits and reusable components. Accelerates delivery across multiple product teams and business units. Partners with security to model threats and mitigate risks (prompt injection, data exfiltration, model poisoning, adversarial inputs). Establishes human workflows for review, override, and continuous improvement. Coaches engineers and data scientists on AI architecture patterns, evaluation methods and deployment practices. Prepares executive ready artifacts, communicates tradeoffs, risks, cost models, and ROI, ties technical decisions to outcome based KPIs. Ensures accessibility, localization, and inclusive design considerations for conversational and generative experiences.  Required Qualifications:5+ years of progressive experience in data engineering, AI/ML engineering, solution architecture or related roles, with at least 3-5 years focused on enterprise scale AI/ML or generative AI initiatives Proven track record designing and delivering end to end AI architecture in medium sized organizations, including reference blueprints, integration patterns, scalable deployment models, governance frameworks, and migration roadmaps to product AI systems. Deep expertise in modern generative AI and LLMs, including RAG architectures, fine-tuning/PEFT, agentic workflows, prompt engineering, inference optimization, evaluation techniques, and LLMOps/MLOps best practices. 5+ years of hands-on proficiency with Databricks platform (Delta Lake, Unity Catalog for governance, Mosaic AI/Databricks AI/BMLflow for ML/GenAI pipelines, Spark for distributed processing) and data lake/lakehouse architectures for handling structured, semi-structured, and unstructured data at enterprise scale. Strong experience building and optimizing data pipelines, vector search/embeddings, ETL/ELT processes, and data governance in lakehouse environments to support reliable AI training and inference. Advanced programming skills in Python (primary), with working knowledge of SQL, Scala, and modern AI development tools such as Cursor, Claude, Devin AI, Jupyter/Databricks notebooks, and Git for collaborative workflows. Solid understanding of cloud platforms (Azure preferred), containerization (Docker/Kubernetes), CI/CD pipelines, GPU/accelerator optimization, and cost-efficient scalable AI infrastructure. Experience with AI governance, security, compliance (data privacy, ethical AI, model monitoring/observability), risk assessment, and alignment of AI solutions with enterprise standards and regulations. Preferred Qualifications:Experience leading cross-functional teams (data scientists, engineers, product, compliance) in PoCs, technology evaluations, AI adoption programs, and stakeholder presentations to executive audiences. Familiarity with emerging AI trends, hybrid/multi-cloud setups, and tools for rapid prototyping/iteration in enterprise settings. Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related quantitative field Strong communication and strategic skills to translate complex technical architectures into business value for C-level stakeholders. Other Qualifications:Successfully pass background check for cybersecurity site access. Architects AI solutions from discovery through production that result in measurable business value. Translates business problems into reference architectures spanning data ingestion, model development and selection, machine learning operations, security and governance, and system integration Designs patterns for LLM/RAG/agentic workflows, event driven and real time use cases and multimodal experiences.  Handles build vs buy analyses, vendor and platform evaluations, and proof of concepts; confirms observability for safety, reliability, drift, basis and performance. Partners with product, data science, engineering, cloud, security and domain stakeholders to deliver solutions that improve outcomes, efficiency and user experience across enterprise functions. Cybersecurity Role Expectations:Candidate will be responsible for reviewing policies and procedures related to cybersecurity and those relevant to the functions of their role.Candidate is expected to maintain a cybersecure work environment.Physical Requirements:Must be able to sit and stand for extended periods of time.Must be able to use hands to type, handle products, tools and navigate a computer keyboard.Must be able to view computer screen for extended periods of time.Specific vision abilities required by this job include close vision and distance vision.Benefits:Medical, Vision, Dental InsuranceHHealth Savings Account with Employer contributions401(k) with Employer matchShort-term & Long-term Disability CoverageAccidental Death & Dismemberment CoverageLife Insurance Coverage80 hours of Paid-Time-Off annuallyEight paid holidays per yearAll other benefits required by applicable law