Member of Technical Staff, Cost Governance

Dipp AI Technologies, Inc.; New York (NY); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Equity vesting

Health coverage

Hardware budget

Pricing influence

Hybrid collaboration NY

401(k) plan

Job summary

Dipp AI Technologies is building Orcher's Cost Governance component, delivering pre-commit controls, cost estimation before execution, and ceilings for agents, roles and workflows in a live AI economy.

You will work on metering, routing across frontier APIs and open-weight models, plus evidence recording and anomaly detection to keep budgets aligned with policy in a distributed, cloud-agnostic environment.

Qualifications

• Strong backend and distributed-systems engineering, especially around counters, quotas, concurrency and partial failure.
• Quantitative fluency with unit economics, forecasting, optimization or capacity planning.
• Experience with billing, metering, rate limiting, marketplace pricing, cloud cost or resource scheduling.
• Ability to reason about quality, latency, privacy and cost as a constrained routing problem.
• A bias toward explicit invariants, testable controls and explainable decisions.

Responsibilities

• Build pre-execution cost estimation and hard spending ceilings for agents, roles, workflows and organizational units
• Develop quality-aware routing primitives across frontier APIs, open-weight models and heterogeneous compute providers
• Design metering that reconciles tokens, tool calls, accelerator time, storage, retries and provider-specific charges
• Detect runaway loops, retry storms, budget drift and anomalous consumption early enough to halt safely
• Record selected routes, alternatives considered, ceilings applied and actual cost in the verified evidence chain
• Partner with customers to translate financial policy into controls that engineering teams can operate

Skills

Backend engineering

Distributed systems

Unit economics

Forecasting

Billing & metering

Education

CS/Engineering/Economics degree

Pricing, metering coursework

Job description

Build the real-time budget, routing and enforcement systems that make AI economics governable before spend occurs.

The cost of an AI workflow is a consequence of architecture: which model handled each step, how much context moved, how many retries occurred, where compute ran and whether an agent was allowed to continue. Reporting the bill afterward is not governance.

You will build Orcher's Cost Governance component: the pre-commit controls that translate enterprise budgets and risk tolerance into enforceable ceilings. This includes cost estimation before execution, per-role and per-workflow budgets, loop and retry controls, quality-aware model routing, anomaly detection, and an evidence record explaining why a route was selected over its alternatives.

The work sits at the intersection of distributed systems, model inference economics and enterprise financial control. A successful system must remain correct while provider prices change, token accounting differs, usage arrives late and workflows span hosted models, open weights, neoclouds and private infrastructure.

What you will do

• Build pre-execution cost estimation and hard spending ceilings for agents, roles, workflows and organizational units
• Develop quality-aware routing primitives across frontier APIs, open-weight models and heterogeneous compute providers
• Design metering that reconciles tokens, tool calls, accelerator time, storage, retries and provider-specific charges
• Detect runaway loops, retry storms, budget drift and anomalous consumption early enough to halt safely
• Record selected routes, alternatives considered, ceilings applied and actual cost in the verified evidence chain
• Partner with customers to translate financial policy into controls that engineering teams can operate

What we look for

• Strong backend and distributed-systems engineering, especially around counters, quotas, concurrency and partial failure
• Quantitative fluency with unit economics, forecasting, optimization or capacity planning
• Experience with billing, metering, rate limiting, marketplace pricing, cloud cost or resource scheduling
• Ability to reason about quality, latency, privacy and cost as a constrained routing problem
• A bias toward explicit invariants, testable controls and explainable decisions

Experience

• 6+ years in platform, infrastructure, billing or financial-systems engineering
• Built or operated a system where inaccurate metering, quota enforcement or allocation had material consequences
• Experience with model serving economics, FinOps or optimization systems is valuable but not required

Education

• Degree in computer science, engineering, mathematics, economics or a related field, or equivalent shipped work
• Quantitative coursework or equivalent applied work in pricing, metering or unit economics is valued.

Compensation and benefits

• Equity with a standard four-year vest and early-stage upside
• Health, dental and vision coverage
• Company-provided hardware and research budget
• Direct influence over Orcher product architecture and pricing primitives
• Hybrid collaboration with the founding team in New York
• 401(k) with company contribution and an annual learning budget.