Senior Solutions Architect - Human Data Services (Generative AI)

Job Description

Role - Senior Solutions Architect (Human Data Services - Generative AI)

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Compenstaion - $160,000 - 190,000 OTE (base + variable)

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At iMerit , we help some of the world's leading AI and technology companies build accurate, reliable, and scalable AI solutions. Our expertise spans high-quality AI data, human-in-the-loop workflows, and enterprise AI applications, enabling organizations to accelerate the development of cutting-edge AI systems. If you're passionate about shaping the future of Generative AI and enjoy solving complex technical challenges, we'd love to hear from you.

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About the Role

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We’re looking for a Senior Solutions Architect – Human Data Services (Generative AI) to design and stand up human-in-the-loop data systems for frontier AI labs and enterprise ML teams .

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You’ll work across SFT, RLHF, evaluation, red teaming, multimodal annotation, and agentic product deployments . The work is highly hands-on: defining task schemas, quality frameworks, and data specifications, and ensuring these workflows operate effectively in production.

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This role sits at the intersection of pre-sales, solution design, and early delivery . You’ll need to be technically credible with ML researchers, comfortable working hands-on with data and tooling, and able to make thoughtful trade-offs across quality, cost, and speed .

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You’ll also apply these capabilities to enterprise AI deployments , including regulated environments, with particular relevance to Banking, Financial Services, and Insurance .

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What You’ll Do

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Solution Design & Pre-Sales

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• Translate ambiguous frontier AI use cases into scoped, buildable data workflows.
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• Map enterprise AI use cases to data, evaluation, and human-in-the-loop requirements, including regulated or high-stakes deployments.
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• Design end-to-end workflows covering task schemas, guidelines, quality frameworks, sampling strategies, and delivery models.
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• Lead technical discovery and identify constraints around data availability, task design, talent requirements, and tooling.
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• Produce clear proposals that align scope, pricing, and delivery assumptions.
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Data Quality & Evaluation

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• Build quality frameworks, including rubrics, acceptance criteria, and audit models.
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• Design evaluation approaches for subjective and high-ambiguity tasks, including reasoning, multimodal, and safety/policy use cases.
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• Contribute to red teaming and adversarial testing aligned with deployment risks.
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Hands-On Execution

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• Analyze datasets, validate outputs, and debug workflows.
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• Prototype task designs and evaluation pipelines using Python, Ango Hub, or client tooling .
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• Partner with Delivery teams to stand up workflows and remain engaged through pilot and early production.
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Client & Internal Leadership

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• Act as the technical counterpart to ML researchers, product leads, program managers, and enterprise stakeholders.
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• Drive alignment across Sales, Solutions, Product, and Delivery .
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• Contribute to reusable patterns for workflows, pricing, and quality frameworks.
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Experience

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• 5–10 years of experience in AI/ML data systems or human-in-the-loop environments, or an advanced degree plus 3–5 years of relevant experience.
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• Experience across at least two of the following:
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• Annotation
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• Data generation/collection
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• Evaluation
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• RLHF
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• Red teaming
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• Client-facing experience in a technical role.
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Technical Skills

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• Strong Python skills with the ability to analyze datasets, prototype workflows, and debug issues.
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• Comfortable working with unstructured and multimodal data , including text, image, PDF, audio, and video.
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• Strong understanding of AI/ML operations , particularly evaluation, fine-tuning, and agentic deployments.
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GenAI & Quality

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• Experience with GenAI data programs, including SFT, preference data, evaluations, and red teaming .
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• Strong understanding of quality frameworks, including:
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• Rubrics
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• Scoring
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• Sampling
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• Audit
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• Adjudication
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• Ability to reason about ambiguity, subjectivity, and model behavior.
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Nice to Have

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• Research background ( PhD or equivalent ) in linguistics, STEM, or social science.
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• Experience designing or deploying AI/ML solutions in Banking, Financial Services, Insurance, or other regulated enterprise environments .
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• Experience working directly with frontier AI labs .
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• Experience with agentic systems .
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