Solutions Engineer

Prolific is an innovative company reshaping AI development through human data infrastructure. As a Solutions Engineer, you will act as a trusted advisor throughout the pre-sales process, collaborating with AI labs and enterprise customers to articulate the value of Prolific's offerings and ensuring a seamless transition to post-sales teams.

Responsibilities:

• Conduct deep discovery sessions with AI researchers, technical program managers, and enterprise stakeholders to understand workflows, pain points, and strategic objectives
• Qualify opportunities and partner closely with Account Executives to build shared deal strategies that create customer trust and accelerate deal momentum
• Deliver customized demonstrations and presentations that articulate value and competitive differentiation for both technical and non-technical audiences
• Design tailored, compelling solution proposals that directly address each customer’s unique evaluation or business needs, translating complex requirements into clear, high-impact proposals
• Collaborate with Account Executives and Services teams to build accurate, solution-specific pricing estimates—factoring in variables such as servicing needs, domain expertise requirements, task complexity, and participant time to ensure cost is clearly understood and credibly packaged into the proposal
• Drive the completion of RFPs, RFIs, and security questionnaires in collaboration with legal and engineering teams
• Serve as the primary technical point of contact during the sales cycle, addressing complex questions related to data security, privacy, platform architecture, API integrations, participant quality and solution design
• Consult on study design, technical setup, and participant calibration. Define success criteria upfront and provide ongoing guidance alongside your services counterparts to ensure pilots are positioned for outcomes that support a confident path to full engagement
• Lead the pre-sales process, partnering as needed with Services and Delivery leads throughout to ensure they are informed and aligned — and own a thorough handoff at Closed Won, documenting requirements, success criteria, and scope commitments clearly
• Remain available to post-sales teams for clarification on what was scoped or sold during early delivery, without ongoing delivery responsibility
• Participate in customer retros and ongoing delivery check-ins to identify gaps between sold and delivered value, feeding insights back into future solutioning
• Serve as the voice of the customer internally—translating patterns from discovery and competitive conversations into actionable insights that influence product roadmap, solutions design, and integration feasibility discussions with engineering
• Partner with product and engineering to evaluate feasibility of custom integrations and emerging use cases raised during the pre-sales process
• Stay current with developments in AI research, RLHF, synthetic data, and the broader ecosystem—sharing competitive intelligence and market trends with the team to sharpen positioning and inform go-to-market strategy
• Bring a growth mindset to every engagement, continuously building expertise in AI techniques, human feedback methodologies, and customer industry dynamics

Requirements:

• 4+ years in a customer-facing solutions engineering, consulting, or pre-sales role within a SaaS or data/AI environment
• Demonstrated experience working with both frontier AI/research organizations and enterprise customers across a full sales cycle
• Strong understanding of API design, web technologies, data transfer and security protocols, and cloud architecture
• Exceptional verbal and written communication skills with the ability to translate complex technical concepts clearly for executives, researchers, developers, and program managers alike
• Proven ability to scope and execute proof-of-concept projects, manage pilot programs, and navigate technical validation activities
• Experience owning a clean pre-to-post-sales handoff — able to document scope, expectations, and success criteria clearly for delivery teams at the point of deal close
• A collaborative spirit and ability to work cross-functionally with product, engineering, and go-to-market teams
• An appetite for continuous learning and problem solving; you actively seek out new knowledge, adapt quickly to change, and bring creative thinking to customer challenges
• Passion for AI and genuine curiosity about the evolving role of human feedback in model development
• Willingness to travel as needed for client meetings and internal events