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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, NetSuite), CRM, ITSM (ServiceNow), supply chain/WMS, or data platforms (Snowflake, Databricks).
• Proven ability to scope and estimate technical work and defend the estimate with clients.
• Excellent communication and presentation skills with both technical and executive audiences.
• Comfortable operating in an early-stage practice: ambiguity, speed, and building the playbook as you run it.

Bonus Points:

• Experience with Model Context Protocol (MCP) or building production agent/connector integrations.
• Background in the NetSuite ecosystem or ERP consulting.
• Experience in a delivery role (you've built what you sell) or a quota-carrying pre-sales role.
• Familiarity with AI governance, security review processes, and enterprise observability tooling.
• Vertical depth in manufacturing, distribution, consumer goods, or food & beverage.