Role Description The Forward Deployed Engineer (FDE) is a senior, hands-on technical role embedded with Alteryx’s most strategic enterprise customers and partners. Your mission is to make Alteryx One a core part of modern data and AI architectures by turning existing analytics workflows into AI-ready, cloud-native solution patterns that scale through partners. This is not a traditional professional services or slideware architect role. As an FDE, you will design, build, and validate real production systems, then package what works into repeatable patterns that partners can sell and deliver independently. What You’ll Do - Design and build AI-ready data architectures using Alteryx One, anchored to cloud data platforms such as Snowflake, BigQuery, Databricks, and AWS - Convert existing analytics workflows into deployable solution patterns that can be reused across customers - Deliver lighthouse customer deployments that move from pilot to production in ~90 days - Partner closely with systems integrators and consulting partners to enable partner-led delivery - Work alongside Sales Engineers and Product teams to validate solutions in production and provide structured product feedback - Create documentation, reference architectures, and playbooks so solutions can scale without ongoing FDE involvement What You’ll Own - Technical leadership from architecture → pilot → production → partner handoff - Architecture decisions for cloud data platform and analytics modernization - Creation of repeatable patterns that drive faster time-to-value, expansion, and consumption - Clear exit criteria for every engagement—success is partner-led delivery, not long-term dependency What Success Looks Like - Success in this role is measured by what reaches production, what scales, and what continues without your direct involvement. - Ship production systems - Move enterprise customers from existing analytics workflows to AI-ready, cloud-native architectures built on Alteryx One - Take solutions from pilot to production in ~90 days - Create scalable solution patterns - Design architectures, workflows, and deployment models that are reused across customers - Establish repeatable patterns that become reference implementations - Enable partner-led delivery - Hand off solutions to systems integrators and consulting partners with clear ownership and exit criteria - Ensure partners can sell, implement, and extend solutions independently - Drive faster customer outcomes - Reduce time-to-production for analytics and AI initiatives - Deliver measurable impact, including cost reduction, faster insights, and improved operational efficiency - Shape the product with real-world evidence - Provide clear, structured feedback based on live deployments - Influence roadmap and product direction by validating solutions in production What You Bring - 7+ years building data, analytics, or platform systems in production - Hands-on experience with at least one major cloud data platform (Snowflake, BigQuery, Databricks, Redshift, or AWS) - Experience working directly with enterprise customers in a technical, field-facing role Technical Skills - Strong background in analytics workflows, data pipelines, or analytics engineering - Comfortable writing production workflows and lightweight code (primarily Python and SQL; APIs as needed) - Solid understanding of cloud architecture, governance, and cost tradeoffs Ways of Working - Builder mindset—you prefer shipping real systems over creating slides - Comfortable operating in ambiguity and giving candid technical guidance - Motivated by scale, reuse, and partner leverage rather than one-off wins Compensation - Base salary range for this role in the United States is $202,500-$225,000 with On-Target-Earnings range of $270,000-$300,000. - A monthly Connectivity Plus stipend of $150 to support remote work-related expenses - An annual $200 home office reimbursement Benefits - Medical, dental, and vision coverage - 401(k) with company match - Paid parental leave, caregiver leave, and flexible time off - Mental health support and wellness reimbursement - Career development and education assistance

Role Description This is a remote position. Owns the eval harness and quality gate from the beginning. This role replaces the old late-stage “Evals Specialist” model with a standing owner for measurable agent quality. Key Responsibilities - Build and maintain the MVP eval harness: golden tasks, exception tasks, scorecard metrics, and regression packs. - Wire evals into CI so quality regressions fail builds and releases. - Define and maintain release-gate thresholds with Product and the Tech Lead. - Lay the path for later adversarial and drift-testing expansion without overbuilding MVP scope. Qualifications - Experience evaluating ML, LLM, or non-deterministic systems. - Strong test and benchmark design capability. - Comfort working with noisy metrics, thresholds, and probabilistic behavior. - Good scripting and automation skills. Requirements - Uses AI to generate candidate eval cases and failure hypotheses, but never confuses generated tests with validated quality. - Approaches AI quality as an operating system, not a QA afterthought. What Success Looks Like in the First 90 Days - The first reference agent has a published scorecard and gated eval path. - Golden and exception tests run automatically. - The team can explain what “good enough to ship” means in measurable terms.

Role Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Senior Software Engineer Expert Type: Contract Compensation: $80–$130/hour Location: Remote Role Responsibilities - Design, develop, and maintain full-stack applications using Python. - Build and integrate APIs and MCP-based systems. - Collaborate closely with engineering and product teams to enhance system scalability. - Write clean, scalable, and production-ready code for robust application performance. - Troubleshoot, optimize, and improve application performance. - Participate in architecture and technical design discussions to drive innovation. Qualifications - Multiple years of experience as a Full Stack Developer. - Strong proficiency in Python. - Experience with MCP and API development. - Ability to work at least 8 hours per day. - Experience building and maintaining production-grade applications. - Strong problem-solving and communication skills. Application Process - Upload resume - AI interview based on your resume - Submit form Resources & Support - For details about the interview process and platform information, please check: Interview Process - For any help or support, reach out to: support@mercor.com - Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Role Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Chemistry Expert (PhD) — AI Safety Type: Contract Compensation: $65–$70/hour Location: Remote Commitment: 15–40 hours/week Role Responsibilities - Write expert-level prompts across specialized chemistry topics. - Evaluate and annotate model responses for scientific accuracy, helpfulness, and appropriate handling of sensitive content. - Apply structured guidelines to classify prompts and conversations. - Collaborate with AI research teams to improve model training and safety. - Work independently and asynchronously to meet deadlines and enhance AI model performance. Qualifications - Must-Have: PhD in chemistry or a closely related field — ongoing or completed. - Deep familiarity with modern laboratory and computational techniques in your subfield. - Strong scientific reasoning and writing in English. - Sound judgment around chemical safety and the responsible handling of dual-use information. - Preferred: Research or coursework on chemical safety/security, synthesis, or hazardous-materials handling. - Experience reviewing, grading, or red-teaming technical content. Requirements - Start Date: Immediate Application Process - Upload resume - AI interview based on your resume - Submit form Resources & Support - For details about the interview process and platform information, please check: Interview Process - For any help or support, reach out to: support@mercor.com - PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.