Technical Program Operations Lead – AI Engineering

Gramian Consulting

. Own end-to-end program delivery across scope, timelines, quality, throughput, contributor performance, and cost.

Posted 9/30/2026contractRemote • India, Pakistan, Indonesia, Kenya, Nigeria, TurkeySeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in program delivery, managing workflows, and improving operational efficiency in software engineering environments. Proficient in utilizing data analytics and programming languages to enhance quality control and contributor management.

Highest-signal resume keywords

Program Delivery ManagementWorkflow Design and ManagementData Analysis and Quality ControlCustomer-Facing CommunicationDistributed Team Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLTypeScriptJavaGoData AnalysisQuality ControlPerformance MetricsOperational ReviewsTechnical Program Management

Soft Skills

Analytical Problem-SolvingCommunication SkillsMentoringExpectation ManagementRelationship Building

Industry Keywords

Software EngineeringTechnical OperationsContributor NetworksMulti-Stakeholder ProgramsOperational Bottlenecks

Tech Stack

Tools & technologies

JavaPythonSQLTypeScriptGo

About the role

Key responsibilities & impact

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

What you’ll need

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.