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≈ $164k – $284k per year (Estimated)
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Remote (United States, Brazil, Colombia, Egypt, Bangladesh, Ghana)also open in India, Indonesia, Kenya, Nigeria, Pakistan, Turkey +1
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Confirmed on the employer's own hiring board on Oct 1, 2026. First seen by Alion on Sep 29, 2026.

Overview
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Gramian Consulting Group is an international management and technology consulting firm based in Los Angeles, California. The firm provides executive-level advisory services, digital transformation strategy, software engineering, and corporate restructuring for middle-market and enterprise clients across diverse industries. By combining high-level strategic planning with hands-on technology execution, the company helps client organizations modernize their operations, optimize revenue models, and scale business growth efficiently.

About Gramian

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.

About the Role

We are looking for an experienced Technical Program Operations Lead to own the production systems behind large-scale AI and software-engineering data programs. You will turn complex research requirements into predictable delivery across quality, throughput, contributor performance, timelines, and cost.

Programs may include coding datasets, repository-level tasks, agentic trajectories, reinforcement-learning environments, benchmarks, code reviews, and rubric-based evaluations. This is an operations leadership role with a strong technical bar, requiring the ability to inspect code, understand tests, analyze quality signals, and improve workflows at scale.

Key Responsibilities

  • Own end-to-end program delivery across scope, timelines, quality, throughput, contributor performance, and cost.
  • Design and manage workflows for coding datasets, agentic trajectories, RL environments, benchmarks, and rubric-based evaluations.
  • Identify operational bottlenecks and improve workflows through better instructions, sequencing, incentives, review systems, and capacity planning.
  • Define contributor requirements and partner with talent teams to source, assess, onboard, train, and ramp distributed software engineers.
  • Build team-lead and reviewer structures for programs involving 100-1,000+ contributors.
  • Own quality-control systems and analyze datasets to identify trends, systematic errors, and root causes.
  • Act as a primary customer contact for AI labs, communicating progress, risks, quality trends, and recovery plans.
  • Translate research objectives into practical task specifications and challenge requirements when they may not produce the intended evaluation signal.
  • Use Python, SQL, or similar tools to automate quality sampling, defect analysis, throughput reporting, and operational reviews.
  • Convert successful workflows into reusable playbooks, quality controls, evaluation assets, and contributor-management systems.
  • Share operational learnings and mentor other program leads.

Requirements

  • Proven experience leading complex, multi-stakeholder programs in software engineering, technical program management, consulting, finance, startups, operations, or a similar environment.
  • Strong analytical and problem-solving skills, including the ability to identify bottlenecks, define meaningful metrics, and improve production performance.
  • Experience managing distributed teams, contributor networks, marketplaces, or large-scale technical operations.
  • Strong customer-facing communication skills, including managing expectations, communicating risks, and building long-term client relationships.
  • Ability to read and review code, understand test suites, and independently assess technical work.
  • Working knowledge of at least one programming language such as Python, TypeScript, Java, or Go.
  • Experience using data and operational metrics to monitor quality, throughput, performance, and delivery.
  • Ability to operate effectively in environments where research requirements and priorities evolve quickly.
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