Company
AI SaaS
SolutionsEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Solutions Engineer. Skills: Solutions Engineering, Technical Account Management, Sales Engineering, Implementation, client-facing technical roles, SaaS platforms, data integrations, analytics-focused products, enterprise or mid-market client implementations, data flows, APIs, technical onboarding processes, data quality assessment, troubleshooting technical implementation issues, communication skills, project management, client coordination, owning multiple client relationships, problem-solving,”
What You'll Achieve.
driving successful implementations; maintaining data quality; ensuring clients receive ongoing value from the platform; long-term platform adoption
Industry & Context.
highly analytical; problem-solving mindset; proactive, solutions-oriented approach; troubleshoot technical challenges; Assess incoming data quality, identify gaps early; work with clients to resolve issues; proactively identify and resolve issues
candidates must be available to work during U. S. business hours aligned with the client’s time zone, available to work during U. S. business hours
What They're Looking For.
Must Have
5–8 years of experience in Solutions Engineering, Technical Account Management, Sales Engineering, Implementation, or similar client-facing technical roles, Experience working with SaaS platforms, data integrations, or analytics-focused products, Experience supporting enterprise or mid-market client implementations, understanding of data flows, integrations, APIs, and technical onboarding processes, Ability to assess data quality and troubleshoot technical implementation issues, communication skills with the ability to work directly with technical and non-technical stakeholders, Highly organized with project management and client coordination abilities, Comfortable owning multiple client relationships and priorities simultaneously, problem-solving mindset with a proactive, solutions-oriented approach, Ability to operate independently in a fast-paced, high-growth environment
Nice to Have
Exposure to marketing analytics, marketing technology, or media measurement platforms is strongly preferred
What You'll Do.
Own the full client technical relationship from onboarding through long-term success
ongoing client partnership across mid-market and enterprise accounts
driving successful implementations
maintaining data quality
ensuring clients receive ongoing value from the platform
Own the full client technical relationship
forecasting model configuration
Lead onboarding scoping by mapping client marketing channels
Assess incoming data quality
and work with clients to resolve issues before downstream impact
Own the client data pipeline from ingestion through modeling outputs and proactively identify and resolve issues
Manage technical implementation and integration processes across client systems and marketing platforms
Ensure client data meets platform standards and modeling requirements
Monitor data flow accuracy
and overall system reliability
Partner with internal engineering teams to troubleshoot technical challenges and improve workflows
Support the sales process through technical discovery conversations and integration scoping
Partner with the sales team to demonstrate product value and technical capabilities to prospective clients
Collaborate cross-functionally with engineering
and client teams to support successful implementations and ongoing account success
Help bridge technical and business conversations to ensure alignment across stakeholders
How You'll Work.
Team & Collaboration
operating cross-functionally between clients, sales, and engineering teams; Partner with internal engineering teams; Support the sales process; Partner with the sales team; Collaborate cross-functionally with engineering, product, and client teams; Help bridge technical and business conversations to ensure alignment across stakeholders
Communication Scope
communication skills with the ability to work directly with technical and non-technical stakeholders; Help bridge technical and business conversations
Process & Methodology
project management, client coordination
Full Job Description
This role is open to candidates based in LATAM, Africa, and Eastern Europe. Please note that as this role supports U.S.-based clients, candidates must be available to work during U.S. business hours aligned with the client’s time zone. Our client is a high-growth AI SaaS platform built for marketers and operations teams. Their core product is a Marketing Mix Modeling (MMM) solution that helps growth teams measure the true impact of advertising channels, optimize budget allocation, and make faster, data-driven decisions. The platform supports media mix modeling, performance tracking, spend optimization, and omnichannel retail measurement to give brands a clear understanding of marketing performance and growth opportunities. LOCATION Fully Remote | 9 AM - 5 PM EST ROLE OVERVIEW The Solutions Engineer will own the full client technical relationship from onboarding through long-term success. This role will focus on client onboarding, data integrations, MMM model setup, forecasting support, technical scoping, and ongoing client partnership across mid-market and enterprise accounts. The ideal candidate is highly analytical, proactive, technically strong, and comfortable operating cross-functionally between clients, sales, and engineering teams. This is not a support-only role — the Solutions Engineer will play a critical role in driving successful implementations, maintaining data quality, and ensuring clients receive ongoing value from the platform. KEY RESPONSIBILITIES CLIENT RELATIONSHIP & ONBOARDING - Own the full client technical relationship, including onboarding, integrations, MMM setup, forecasting model configuration, and ongoing support. - Lead onboarding scoping by mapping client marketing channels, revenue sources, and data ecosystems. - Assess incoming data quality, identify gaps early, and work with clients to resolve issues before downstream impact. - Own the client data pipeline from ingestion through modeling outputs and proactively identify and resolve
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