AI Deployment Lead - Private Markets

TrueSeek; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

TrueSeek in New York, NY is hiring a Deployment Lead to own AI-native data migration and transformation engagements from scoping to go-live. You’ll sit with customers, direct engineers, and ensure outcomes through delivery.

You’ll engage with private equity-backed portfolio companies, drive ERP/CRM migrations, data schema mapping, and cite extraction, ensuring each record is traceable to source and value is realized.

Qualifications

• 3+ years at McKinsey, Bain, or BCG, or in a PE value-creation team.
• Experience leading data migration and AI-driven transformation.
• Strong client-facing and stakeholder management abilities.

Responsibilities

• Lead engagements: scope with stakeholders, direct engineers, own through go-live.
• Present readouts to sponsors and drive follow-on opportunities.
• Build and scale engagements, hiring leads as the customer base grows.

Skills

Engagement leadership

Stakeholder management

AI adoption

Data migration

Client-facing

Tools

ERP systems

CRM systems

SQL

Job description

DEPLOYMENT LEAD | AI-NATIVE DATA MIGRATION & TRANSFORMATION

New York, NY | $150K–$200K + Bonus

THE SHORT VERSION

The founders are running every customer engagement themselves right now, and it's the bottleneck: deals are signing faster than the team can staff them. This role takes that job over: sit with the customer, scope the problem, direct the engineers, own the outcome through go-live.

It's also the part of this business people get hooked on, because you're watching AI do real work inside real, operating companies, not a pilot, not a slide.

WHAT THE COMPANY DOES

Private equity firms bring us into their portfolio companies to run value creation through data and AI. The portfolio company is the buyer; the PE sponsor is the channel that gets us in the door.

• Migration: ERP and CRM migrations, system consolidations. Work that normally goes to offshore teams for 18–24 months, done in weeks.
• Transformation: the unglamorous work before the AI mandate can actually run. Most companies stall because the underlying data was never made usable.

The hard part isn't moving data, it's deciding what it means and proving the final record is right. Ingestion, schema mapping, cited extraction, exception review, reconciliation, controlled writeback. Get it wrong and a customer gets billed for the wrong product, quote-to-cash breaks, a covenant trips. Get it right, every field cited back to source, and that's what customers are actually paying for.

THE JOB, IN THREE PARTS

• Engagements (the core): Run what's signed as engagement lead: scope with the stakeholders who own the systems, direct the engineers, make the calls that keep it moving, own it through go-live. Day one looks like this: a post-M&A migration just closed at a portfolio company, go run it with two engineers.
• Relationships: The work generates the next work. Whoever ran the last engagement is the most credible person in the next room. You'll sit in sponsor conversations, present readouts, and turn one portfolio company into three. No quota, commission is pure upside on anything you bring in.
• The practice (over time): Every engagement shares common building blocks that haven't been productized yet. That becomes yours to own, along with hiring engagement leads under you as the customer base stacks up.

WHO THIS IS FOR

3+ years at McKinsey, Bain, or BCG, or on a PE value-creation team, ideally a few years of consulting followed by a stretch inside PE, or you ran a function inside a portfolio company when the data was a mess.

• You can run an engagement and want to: ambiguous scope, a demanding customer, engineers who need clean decisions
• Operationally excellent: the deck is right, the model ties, the client hears back same-day
• You use AI aggressively, or you're determined to learn fast: 80/20 judgment over polish
• You've seen the path to partner and you'd rather own something instead

If you're operationally strong, you can hold a room full of VPs, and you want to be on the frontier of how real companies adopt AI, this is that seat.