Staff Applied AI Engineer - Pre-Sales

Role overview

This Staff-level position sits at the intersection of applied AI engineering and pre-sales customer engagement. The role partners closely with sales teams and solution practice leaders to run structured technical discovery, scope high-value AI opportunities, and design tailored demos and pilots that show measurable business outcomes. The mission is to help large enterprise customers adopt generative AI and machine learning by translating ambiguous business problems into technically sound, well-scoped engagements that transition cleanly into delivery.

Responsibilities

- Partner with sales and solution practice leaders to shape technical strategy across active prospects, win technical evaluations, and ensure a clean handoff to delivery through structured documentation and expectation alignment. - Lead discovery engagements with prospects covering business objectives, success criteria, data landscape, architectural constraints, security considerations, and organizational readiness. - Translate discovery findings into well-defined GenAI solution architectures that pair internal frameworks with complementary third-party technologies. - Design, build, and deliver bespoke demos and pilots including evaluation pipelines, dataset strategy, retrieval-augmented generation systems, fine-tuning workflows, prompt engineering approaches, and agentic architectures. - Author and contribute to proposals, Statements of Work, and RFP/RFI responses with realistic effort estimates, architectural soundness, and clear scope boundaries. - Systematically convert reusable patterns from bespoke demos into reference architectures, demo assets, benchmarks, and internal solution playbooks. - Travel up to 25% annually to support customer engagements.

Requirements

- Bachelor's degree in Computer Science, Engineering, Math/Statistics, or equivalent practical experience. - 8+ years in customer-facing technical roles such as pre-sales, solutions engineering, or applied AI, including discovery, scoping, demos, proof-of-value work, and RFP responses. - Strong Python skills with hands-on experience across the modern GenAI stack including LLM ecosystems, RAG, vector databases, evaluation workflows, orchestration frameworks, and agent authoring tools. - Background in the predictive ML stack including classical ML libraries such as scikit-learn and data processing frameworks such as pandas or Spark. - Demonstrated ability to operate in fast-paced environments and rapidly prototype ML solutions, RAG systems, prompt-based workflows, fine-tuned models, and agentic systems. - Experience estimating scope and producing technical content for proposals and Statements of Work.

Nice to have

- Ability to translate ambiguous business problems into testable technical approaches with measurable success criteria. - Strong presentation and storytelling skills with credibility across both technical and executive audiences.

Benefits and work setup

- Compensation range of $190,000 to $300,000 OTE, plus equity in the form of employee stock options. - Office hubs in New York, San Francisco Bay Area, Austin, Dallas, Seattle, Atlanta, Nashville, and Boston, with remote-US eligibility. - Up to 25% annual travel. - Reasonable accommodations available for candidates and employees with disabilities.