Director Pre-Sales & AI Data Solutioning

Shaip Ai Data (india); Ahmedabad District; On-site; INR 3,500,000 - 7,500,000; Full time

Job summary

Shaip by Ubiquity is seeking a hands-on Director to lead its Pre-Sales and VMS Pre-Sales teams. The candidate will translate enterprise customer requirements into executable AI data solutions, orchestrating feasibility, delivery designs, vendor inputs, cost models, proposals and timelines.

Close collaboration with Sales and operations is essential to align VMS, L&D, core delivery and Physical AI delivery.

Qualifications

• 8+ years of relevant experience in AI data, data operations or related services
• Demonstrated ownership of large or complex customer proposals and cost models
• Fluency in at least two major AI data domains; familiarity with crowd/vendor models and QA

Responsibilities

• Lead Pre-Sales and VMS Pre-Sales teams; coach managers and specialists and develop capabilities
• Drive discovery with enterprise customers; translate use cases into requirements and acceptance criteria
• Coordinate feasibility, delivery designs, vendor inputs, cost models, proposals and timelines
• Own comprehensive bottom-up cost models; pricing recommendations and margins; contribute to RFPs and SOWs
• Deliver signed-off solution packs to Delivery and VMS; track cost/margin and win/loss insights

Skills

AI data

Data operations

Proposal leadership

Commercial judgment

Job description

The opportunity

Shaip by Ubiquity is seeking a hands‑on Director to lead its Pre‑Sales and VMS Pre‑Sales teams. The Director translates enterprise customer requirements into executable AI data solutions, orchestrating feasibility, delivery designs, vendor inputs, cost models, proposals and timelines. The position partners closely with Sales and with the other operational deputies responsible for VMS & L&D, core delivery and Physical AI delivery.

Key accountabilities

Leadership and operating cadence

• Lead the Pre‑Sales and VMS Pre‑Sales teams; coach managers and specialists, allocate work and own capability development.
• Establish one intake process, bid prioritization, turnaround SLAs, templates, approvals, handoff standards and a proposal performance dashboard.

Customer discovery and solution design

• Lead discovery with enterprise customers and Sales; convert use cases into detailed statements of requirements, acceptance criteria and dependencies.
• Design collection, annotation, speech/audio, healthcare, GenAI evaluation/RLHF, computer‑vision and physical‑AI data workflows as applicable; coordinate product, engineering and security inputs.

Feasibility and operating model

• Work with VMS & L&D and Delivery to validate vendor/contributor availability, training, geographies, tooling, capacity, productivity, quality and delivery schedules.
• Evaluate competing delivery models, pilots, security/data residency constraints, risks, contingencies and explicit assumptions; do not make unvalidated commitments.

Costing and commercial proposal

• Own comprehensive bottom‑up cost models covering supplier rates, labor productivity, onboarding/training, QA, rework, tooling, management overhead and delivery risk.
• Own pricing recommendations, scenario/sensitivity analysis and proposed gross margins; obtain leadership approval for final external pricing and exceptions.
• Lead technical/commercial inputs to RFPs, RFQs, pilots, proposals and SOWs, including pricing units, scope, milestones, acceptance, exclusions and change control.

Handoff and improvement

• Deliver signed‑off solution packs to Delivery and VMS; document bid assumptions and named operational owners.
• Track quoted versus realized unit cost/margin and win/loss insights to improve future solutioning and estimation.

Candidate profile

• 8+ years of relevant experience; strong evidence of leading AI data, data operations, or related services solutioning is more important than years alone.
• Demonstrated personal ownership of large or complex customer proposals, cost models, vendor feasibility, delivery designs and team leadership.
• Working fluency in at least two major AI data domains, with ability to learn others rapidly; familiarity with global crowd/vendor models and quality assurance.
• Strong commercial judgment: pricing units, gross margin, change control, rework, rate/throughput sensitivity and deal‑risk tradeoffs.