Role Description A Solutions Engineer at DigitalGenius works in post-sales, partnering closely with Product and Customer Success Managers (CSMs) to design, implement, and optimize AI-driven customer service solutions for our clients. You are the technical owner of customer implementations, ensuring every solution is scalable, secure, high-performance, and aligned with both business goals and our platform's capabilities. You'll spend your time turning messy real-world e-commerce problems into reliable AI-powered automations — designing flows, wiring up integrations, writing Python where the platform stops, prompting and evaluating LLMs, and continuously raising the bar on what our AI agents can resolve autonomously. Key Responsibilities - Solution Design & Implementation - Translate business requirements into scalable technical solutions on the DigitalGenius platform - Configure workflows, AI agents, integrations, and automation logic for complex e-commerce use cases - Design and implement APIs and third-party integrations (OMS, carriers, Helpdesk, etc.) - Prompt, tune, and evaluate LLM-powered components — classifications, extractions, guardrails, and generative replies - Technical Ownership (Post-Sales) - Lead new use case implementation projects - Ensure timely, high-quality launches with measurable automation impact - Troubleshoot complex technical challenges across systems, data, and AI behavior - Customer Collaboration - Partner with CSMs to align technical delivery with customer outcomes and ROI - Advise customers on best practices, scalability, AI strategy, and optimization - Support strategic expansions, new channels, and advanced use cases - Product Partnership - Provide structured feedback to Product based on what you see in real implementations - Identify feature and AI capability gaps and contribute to roadmap discussions - Participate in beta testing, model evaluations, and product validation initiatives - Optimization & Innovation - Continuously improve automation performance, resolution rates, and AI accuracy - Proactively identify opportunities for process improvements — both for customers and internally - Contribute reusable assets, documentation, prompts, evaluation sets, and internal best practices - Use AI to automate your own work: build internal tools, scripts, and agents that make the SE team faster and better Qualifications - AI-first mindset. You're genuinely excited about LLMs and applied AI. - Automation / workflow mindset. You can translate business requirements into reliable flows. - Strong API + integration experience (building and debugging). - Python. Hands-on experience writing and shipping Python used by others. - Strong communication. You can explain technical concepts clearly to non-technical stakeholders. - Organization and project management. Strong organizational skills with the ability to manage workstreams. Preferred - Hands-on LLM experience. Prompting, classification, guardrails, evaluation, and tooling. - Low-code / workflow automation experience. Tools like Zapier, Make, Workato, etc. - E-commerce / OMS exposure (especially Shopify). - Customer service platforms. Zendesk, Salesforce Service Cloud, or similar. - SaaS delivery background. Implementations, solutions, or technical support in customer-facing environments. Benefits - Competitive Salary - Generous vacation time (25 days) - Environment to develop your skills without bureaucracy or red tape - Monthly fitness stipend of $210 (Lifestyle wallet) from day 1 - Ongoing subscription to Mental Health Support Platform - Paid Claude subscription — because we want you using the best AI tools every day - Learning budget to invest in courses, books, conferences, and certifications

Title: Specialist Solutions Architect - AI/ML Location: United States, Remote Job Description: P-226 As a Specialist Solutions Architect (SSA) - AI/ML Engineering, you will be the trusted technical ML & AI expert to both Databricks customers and the Field Engineering organization. You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying cutting-edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing yourself as an AI thought leader. The impact you will have: - Architect production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc. - Serve as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems - Build, scale, and optimize customer AI workloads and apply best-in-class MLOps to productionize these workloads across a variety of domains - Provide advanced technical support to Solution Architects during the technical sale, ranging from feature engineering, training, tracking, serving, to model monitoring, all within a single platform, as well as participating in the larger ML SME community in Databricks - Collaborate cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities, and influence the product roadmap, helping with the adoption of Databricks’ AI offerings What we look for: - 5+ years of hands-on industry ML experience in at least one of the following: - ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring. - AI Engineer: Experience with the latest techniques in LLMs & agentic systems, including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI - Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience - Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike - Passion for collaboration, life-long learning, and driving business value through ML & AI - [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role - Can meet expectations for technical training and role-specific outcomes within 3 months of hire - This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. Zone 1 Pay Range $180,000—$247,500 USD Zone 2 Pay Range $180,000—$247,500 USD Zone 3 Pay Range $180,000—$247,500 USD Zone 4 Pay Range $180,000—$247,500 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

• Conduct high-impact, interactive client discovery sessions to uncover deep business pain points, strategic goals, and operational bottlenecks specifically related to financial processes, accounting, and regulatory compliance. • Actively participate in the qualification process, analysing prospect requirements to ensure our Adaptive ERP, and complementary solutions are the perfect engine for their financial needs. • Design, build, and deliver compelling software demonstrations and executive presentations. • Partner with the sales team—acting as a seamless, elite pit crew—to build customised win strategies, craft RFP/RFI responses, and navigate complex technical evaluations. • Maintain a premier level of knowledge regarding QAD’s suite of solutions, financial and accounting industry trends (e.g., IFRS, US GAAP) , and the competitive grid.

• Engage with Solutions Architects to understand use case demand for prioritized customers • Lead post-technical win technical account strategy and execution for key accounts • Be accountable technical leader for customer use cases across teams • Serve as first contact for technical issues related to production/go-live • Leverage shared services, user education, and support for customer success • Create and execute plans to accelerate key use cases into production • Navigate Product and Engineering teams for innovations and support