AI/ML Technical Program Manager (TPM) – Product & Platform

Confidential Hiring Specification

1. The Practice & Platform Context

Espalier is an AI-powered decision-intelligence platform purpose-built for environmental services and infrastructure asset classes. The platform runs on a proprietary industry graph and automated data pipelines covering asset registries, filings, spatial mapping, and transactional signals.

To turn raw intelligence into automated, production-grade products, we are establishing a core Engineering & Product Delivery Pod. We are hiring a hands-on Technical Program Manager (TPM) / AI Product Delivery Lead who bridges the gap between machine learning research, data engineering, and shipping end-to-end commercial software.

2. The Role

Technical Program Manager (AI/ML & Product Engineering)

● Mandate: Own the cross-functional product delivery lifecycle for Espalier’s AI/ML engines from problem scoping to production deployment. This role partners directly with ML engineers, full-stack developers, and commercial Pod leads to translate ambiguous intelligence requirements into scoped, shipped software products.

● Core Ownership:

○ Product Delivery Lifecycle: Drive sprint roadmaps, define PRDs, architect system workflows, and remove blockers across the entire build-to-ship cycle.

○ Hands-on AI/ML Scoping: Formulate data-extraction pipelines (e.g., multimodal extraction, OCR, LLM structured outputs, document intelligence) and predictive modeling workflows with engineering teams.

○ Production Quality & MLOps: Define evaluation harnesses, ground-truth benchmarks, error-budget tracking,



and deployment criteria for production models.

○ Cross-Pod Integration: Align product release milestones directly with vertical Engagement Managers and US commercial delivery timelines.

3. Requirements & Screening

● Experience: 5–8 years total experience, with 3+ years specifically driving AI/ML or data-intensive software products from concept to live production.

● Technical Depth: Must be able to read architecture diagrams, query data (SQL/Python), review ML model trade-offs (precision/recall, latency vs. accuracy, token economics), and debug delivery bottlenecks directly with engineering teams.

Capability Matrix

Capability

What Strong Looks Like

How We Test It

1. AI/ML Pragmatism

Knows what state-of-the-art LLMs, OCR, and ML can and cannot do; avoids hype; designs structured benchmark evaluations.

Stage 1 architecture & ML judgment prompt

2. Hands-on Execution

Writes technical PRDs, maps API contracts, breaks down complex data pipelines, and tracks sprint velocity.

Stage 2 take-home case

3. Systems & Delivery

Anticipates data-drift, edge cases, latency constraints, and deployment hurdles before sprint kickoff.

Case Q&A; & scenario troubleshooting

4. Cross-Functional Bridge





Translates ambiguous market/client needs into concrete engineering tickets; pushes back constructively on both sides.

Stage 1 behavioral & case panel

Screening Grid

Must Have

Strong Plus

Disqualifier

5+ years tracking/shipping technical products; 2+ years hands-on with AI/ML or LLM-based pipelines

Prior background as a software/data/ML engineer or founder; B.Tech/M.S. in CS or related field

"Process-only" or pure Scrum Master profile who cannot read code or query data

Demonstrated track record of shipping zero-to-one B2B SaaS or data products to production

Experience deploying production document-parsing, multimodal pipelines, or graph databases

Has only worked on slide decks, high-level roadmaps, or vendor integrations

Fluency with APIs, system architecture, Python/SQL, and up-to-date CI/CD/MLOps stacks

Experience working closely with US product leaders or enterprise B2B delivery

Low ownership; requires large program-management office (PMO) scaffolding

6. Indicative Compensation & Positioning

Component

Indicative Range (India Benchmark)

Base Salary

₹35L – ₹50L

Performance Bonus

10% – 20%

● Positioning the Offer: Highlight direct technical ownership. Unlike large enterprise IT firms where TPMs serve as ticket coordinators, Espalier gives this leader direct technical mandate over the core AI decision engine, flat-hierarchy engineering partnerships, and meaningful upside equity.

Pay: ₹4,000,000.00 - ₹7,500,000.00 per year

Benefits

- Health insurance
- Leave encashment
- Work from home

Work Location: Hybrid remote in Gurugram, Haryana

📌 Program Manager - AI/ML, Product (Gurugram)
🏢 Espalier
📍 Gurugram