Strategic Project Lead, Software Engineering
$120,000–$200,000 year
On-siteSan Francisco, California, United States
San Francisco, California, United StatesOn-sitePart Time$120,000–$200,000 yearSenior LevelAI ServicesStartup
Part TimeSenior LevelStartupAI Services
Job Summary
Design and manage end-to-end data pipelines from customer specification to final delivery, diagnosing bottlenecks in real time by re-sequencing workflows and scaling review processes. Act as the primary point of contact for researchers and program managers at frontier AI labs, delivering clear reporting and anticipating client needs to build long-term trust. Orchestrate 100–1,000+ contributors by vetting, onboarding, and performance-managing domain experts while implementing gamification systems to maintain engagement. Own quality control across the annotation lifecycle by analyzing datasets for anomalies and fixing root causes rather than symptoms. Document onboarding scripts and quality benchmarks to codify successful practices for future scaling.
Required Qualifications
- Background in consulting, finance, startups, or other operationally intense environments
- Proven track record of managing complex, multi-stakeholder projects
- Strong analytical abilities
- Strong communication abilities
- Customer-facing experience
- Comfortable working directly with high-profile clients
- Ability to manage expectations
- Ability to build long-term relationships
- Excitement for gritty process optimization
- Experience with large-scale execution
- Ability to make complex operations faster, cleaner, and more reliable
- Ability to deliver a project end-to-end with no quality escapes reaching the customer
- Ability to establish a reporting cadence trusted by the lab
- Ability to publish a contributor onboarding playbook
- Ability to know the names of every researcher on accounts
- Ability to manage 300+ active contributors across concurrent workstreams
- Ability to codify a quality framework for daily use by the team
- Ability to manage $5M+ in active project revenue
- Ability to ramp a second SPL off the playbook
- Ability to multiply through others rather than operate as a solo contributor
- Ability to design and manage data pipelines from customer specification to final delivery
- Ability to diagnose bottlenecks in real time
- Ability to re-sequence workflows
- Ability to refine instructions
- Ability to create incentive systems
- Ability to scale review processes
- Ability to run daily war room syncs
- Ability to act as the primary point of contact for researchers and program managers at frontier AI labs
- Ability to deliver clear, consistent reporting
- Ability to proactively anticipate client needs
- Ability to build long-term trust that converts one-off projects into multi-year partnerships
- Ability to identify expansion opportunities
- Ability to source, vet, onboard, train, and performance-manage domain experts
- Ability to maintain high execution standards at every stage of production
- Ability to design motivation and performance systems including gamification
- Ability to own quality control across the annotation lifecycle
- Ability to set the bar, measure against it, and close the gap when it slips
- Ability to analyze datasets to identify trends, anomalies, and systematic errors
- Ability to fix the root cause of issues
- Ability to implement and continuously improve annotation, evaluation, and curation best practices
- Ability to stay ahead of emerging practices in AI data operations
- Ability to champion workflow changes that reduce task completion times and improve cost efficiency
- Ability to maintain clear, scalable documentation
- Ability to document onboarding scripts
- Ability to document quality benchmarks
- Ability to document contributor management frameworks
- Ability to document escalation patterns
- Ability to own a domain's section of the SPL knowledge base
- Ability to actively mentor the next hire
- Ability to coordinate hundreds of distributed software engineers
- Ability to respond quickly to changing research requirements
- Ability to inspect code
- Ability to understand tests
- Ability to interrogate quality signals
- Ability to challenge a workflow or rubric when it is not producing the intended result
- Ability to build and operate the system that consistently produces high-quality technical work at scale
- Ability to turn complex research requirements into predictable delivery across quality, throughput, contributor performance, timelines, and cost
- Ability to handle supervised coding demonstrations
- Ability to handle repository-level tasks
- Ability to handle agentic trajectories
- Ability to handle reinforcement-learning environments
- Ability to handle benchmarks
- Ability to handle code review
- Ability to handle rubric-based evaluations
Desired Qualifications
- Experience with post-training
- Experience with evaluation
- Experience with agentic AI research
- Experience with frontier models training and evaluation
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.