Director of Sales Engineering (Data & AI)

Blue Orange Digital•New York, NY

15d•Hybrid

About The Position

Blue Orange Digital helps organizations unlock measurable business value with modern analytics and AI. We are in a focused growth phase serving Financial Services, Private Equity (PE) firms and their portfolio companies, delivering AI solutions that drive EBITDA uplift, revenue acceleration, and operational efficiency. The Director of Sales Engineering is the technical heartbeat of our sales motion. You own the technical win on every qualified opportunity—running discovery, architecting solutions, delivering demos and POCs, and ensuring proposals are technically compelling and commercially sound. You're the person who translates client pain into solution architecture, makes complex AI concepts tangible through live demonstrations, and gives account executives the technical credibility they need to close. You thrive in the ambiguity of early sales conversations and bring structure through sharp discovery, clear scoping, and pragmatic solution design. This is a hands-on individual contributor role. You won't manage a team—you'll be in the deals, building the demos, shaping the proposals, and winning the technical evaluation.

Requirements

6+ years in Data, Analytics, or AI/ML roles, with 3+ years in sales engineering, solutions architecture, or technical pre-sales
Hands-on proficiency with modern data platforms: Databricks, Snowflake, or equivalent; at least one major cloud (AWS, Azure, GCP)
LLM/GenAI fluency: RAG patterns, vector databases, prompt engineering, LLM evaluation, deployment considerations
Proven discovery skills: Ability to run technical discovery, extract requirements from ambiguous conversations, and translate to solution architecture
Demo excellence: Track record of building and delivering compelling technical demonstrations that advance deals
Strong proposal experience: Authored technical sections of winning proposals; comfortable with RFP response
Communication skills: Can explain complex technical concepts to both technical practitioners and business stakeholders
Python proficiency: Able to build demos, review code, and speak credibly to implementation approaches
Self-directed: Comfortable operating independently, prioritizing across multiple pursuits, and driving outcomes without heavy oversight

Nice To Haves

PE or portfolio company experience—understanding of value creation, hold periods, EBITDA focus
Prior consulting or professional services background
Certifications: Databricks, Snowflake, AWS/Azure/GCP AI/ML
Experience with MLOps/LLMOps tooling and practices
Familiarity with data engineering patterns: ETL/ELT, Lakehouse, streaming, data quality
Exposure to specific verticals: Industrial/Manufacturing, Healthcare, B2B Services, Financial Services

Responsibilities

Technical Discovery & Scoping
Lead technical discovery calls and workshops to understand client challenges, data landscape, and business objectives
Translate business pain into solution architecture—data platforms, AI/ML initiatives, LLM applications, automation
Size opportunities and define scope, assumptions, dependencies, and technical risks
Develop level-of-effort estimates and work with delivery to validate pricing and timelines
Create solution briefs and technical narratives that differentiate Blue Orange from competitors
Identify "land and expand" opportunities within accounts
Proposal & Pursuit Execution
Own technical sections of proposals and RFPs—solution approach, architecture, methodology, team composition
Build pricing models in partnership with delivery leadership
Develop win themes and competitive positioning for each pursuit
Manage technical objections and competitive differentiation throughout the sales cycle
Participate in orals, finalist presentations, and technical deep-dives
Ensure proposals are technically accurate, commercially viable, and aligned to client priorities
Demo & POC Delivery
Build and maintain demonstration environments showcasing Blue Orange capabilities:
Databricks/Snowflake data platforms
LLM applications and copilots (RAG, agents, chat interfaces)
Predictive analytics and ML models
Dashboards and visualization
Design and execute proof-of-concept engagements with clear success criteria
Create reusable demo assets, sample architectures, and reference implementations
Document use cases, patterns, and technical approaches for future pursuits
Sales Enablement & Process
Create battle cards, competitive intelligence, and technical FAQ documents
Train account executives on technical qualification criteria and discovery techniques
Refine discovery methodology, scoping templates, and proposal frameworks
Provide input on go-to-market messaging, service offerings, and market positioning
Contribute technical perspective to marketing content and thought leadership