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Solution Architect - Applied AI Practice; Pre-Sales; Remote

Remote / Online - Candidates ideally in
Denver, Denver County, Colorado, 80285, USA
Listing for: Bryant Park Consulting
Remote/Work from Home position
Listed on 2026-07-23
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 200000 - 250000 USD Yearly USD 200000.00 250000.00 YEAR
Job Description & How to Apply Below
Position: Solution Architect - Applied AI Practice (Pre-Sales) (Remote)

About Bryant Park Consulting:
Bryant Park Consulting is a leading Oracle | Net Suite consulting firm dedicated to helping businesses achieve their goals through successful ERP implementations and optimizations. We are a team of experienced consultants passionate about delivering exceptional client service and driving digital transformation. At Bryant Park Consulting, we foster a collaborative and supportive environment where our employees can thrive and grow professionally.

About

the role

Bryant Park Consulting is building an Applied AI practice — an AI delivery arm that designs, builds, and operates AI agents inside client systems. We are looking for a Solution Architect to own the sales cycle end‑to‑end: sourcing and developing opportunities, leading discovery, scoping and sizing engagements, and translating operational pain points into credible agent architectures. You will be the technical expert and trusted advisor from first conversation through close — whether the entry point is a demo, a workshop, an assessment, or a scoped build.

This role reports to the VP of Sales, with a dotted line to the Applied AI Practice Lead, and, as a pivotal driver of practice growth, carries sales and bookings targets and incentives.

Responsibilities
  • Source and develop opportunities — within existing BPC accounts, through partner channels, and via your own network — and lead the sales cycle end to end, from first conversation through signed engagement.
  • Build and maintain relationships with referral channels:
    Anthropic and other AI vendor sales teams, centers of influence, and partner firms that refer new business to the practice.
  • Lead technical discovery sessions with prospective clients to map their systems, data, and operational workflows to agent automation opportunities.
  • Deliver the right pre‑sales motion for each opportunity — demos from our pre‑built agent fleet, workshops, technical deep dives, or proof‑of‑value scoping — matched to the client's vertical and buying stage.
  • Scope and size engagements: map candidate agent initiatives to complexity bands, estimate work units, and recommend the right engagement structure and retainer tier.
  • Design high‑level agent architectures and solution blueprints — agent design, MCP connector approach, system integration points, security and access model, and observability.
  • Collaborate with sales and Global Solution Architects to qualify opportunities and respond to RFPs.
  • Draft proposals and statements of work — pricing, effort estimates, timeline, and phasing — then present to client stakeholders and negotiate scope, pricing, and redlines through to signature.
  • Translate technical concepts — agents, MCP, model selection, token economics — into language that resonates with CFOs, CTOs, and operations leaders.
  • Handle technical objections credibly: build‑vs‑buy, security and data access, infrastructure and model‑choice concerns, and how production agents differ from the AI tools clients already use.
  • On close, carry the vision into delivery: mobilize the assigned team to deliver what was positioned and sold, and stay engaged as engagement sponsor.
  • Develop long‑lasting client relationships as a trusted advisor, positioning follow‑on services as the account grows.
  • Contribute to demo assets, sales collateral, and reusable solution patterns as the practice's IP library grows.
  • Stay current on the AI agent landscape — models, agent frameworks, MCP ecosystem, and enterprise AI governance trends.
Qualifications
  • Bachelor's or advanced degree in Computer Science, Information Systems, Engineering, or equivalent experience.
  • 4–7 years in a pre‑sales, solution architecture, or technical consulting role with enterprise clients.
  • Hands‑on experience with LLM‑based applications: model APIs (Anthropic, OpenAI, or similar), agent frameworks, prompt and context engineering, and tool/function calling.
  • Strong understanding of enterprise integration — APIs, middleware/iPaaS, event‑driven patterns — and how AI agents connect to systems of record.
  • Experience with enterprise business systems across ERP (SAP, Oracle, Microsoft Dynamics, Net Suite), CRM, ITSM (Service Now), supply chain/WMS, or data platforms…
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