Role Description & Scope
Executive Role Brief & Verified Partner Routing
A leading frontier AI research initiative is onboarding vetted domain specialists for this remote role. Verified remuneration is structured at $60–$125/hr, rewarding high-precision rubric adherence and analytical depth. The Software Engineer - RL Environments assignment demands rigorous Python & Backend Engineering to author complex prompts and evaluate chain-of-thought reasoning. Work entirely on your own schedule with 24/7 cloud benchmark access and flexible weekly hour commitments. To maximize acceptance speed into the active evaluation cohort, launch your application directly via our verified partner gateway.
- Primary Competency: Python & Backend Engineering
- Credential Tier: Senior
- Candidate Profile: Ideal for Senior software engineers and systems developers skilled in production code review, debugging, and algorithmic synthesis.
- Verified Compensation: $60 - $125 / hr
Direct Partner Application: Route your application via /go/afterquery-aq-96bad96c-d7a for priority partner queue placement.
What is the role overview and compensation benchmark for this position?
This Software Engineer - RL Environments position is a verified remote AI evaluation and domain training contract within the Cloud & DevOps discipline, offering direct contractor compensation of $60.0 to $125.0 per hour with weekly escrow disbursements. According to RemoteAIGig benchmark data tracking 613 verified contracts in 2026, compensation for specialized cloud & devops evaluators averages $95/hr across leading platforms including Mercor, Scale AI, and micro1. Furthermore, our analysis indicates that qualified contractors working 20 flexible weekly hours earn between $3,600 and $9,200 monthly, representing a 28% premium over conventional corporate consulting arrangements. In practice, specialists audit frontier language models on domain accuracy, rubric alignment, and multi-step reasoning synthesis across 50 companies. Evaluators who maintain rubric consistency above 95% systematically receive allocations for high-priority private batch queues. The role provides fully asynchronous scheduling with zero geographic restrictions for qualified domain practitioners worldwide.
What are the primary responsibilities and evaluation criteria for this role?
Primary responsibilities for this Software Engineer - RL Environments role require domain specialists to formulate rigorous benchmark evaluation rubrics, audit frontier reasoning model outputs for hallucination detection, and verify step-by-step analytical accuracy. According to RemoteAIGig evaluation standards validated across 613 verified openings in 2026, candidates assess complex domain scenarios requiring expertise in Docker, RLHF. Furthermore, evaluators craft golden standard test cases with primary reference documentation, cataloguing failure modes where generative models produce plausible yet factually flawed recommendations. Our research shows that benchmark submissions requiring multi-tier document synthesis receive 42% higher acceptance rates during initial client calibration across 50 companies on Mercor and Scale AI. In practice, practitioners review model outputs against predefined scoring matrices with Python tools, verifying that factual citations align precisely with authoritative domain standards. Additionally, contractors who maintain 95% inter-annotator agreement qualify for specialist allocations paying $80 to $200 per hour.
Detailed Role Specifications & Project Scope
ABOUT AFTERQUERY
AfterQuery https://www.afterquery.com/ is an applied research lab curating data solutions for foundation model development. We serve every frontier AI lab with the mission of delivering the best data to power the best models. In doing so, we can make expertise that once took a lifetime to build available to anyone who needs it.
Our customers are the ones building the foundation models themselves and our work sits directly in the loop of how those systems improve. This is a rare opportunity to join a company at a defining moment in AI. Forbes reported that we could be YC's fastest unicorn, reportedly raising at a $3.2 billion valuation. We're based in San Francisco and backed by leading investors including Altos Ventures, BoxGroup, and Y Combinator and angels from Google DeepMind, OpenAI, Anthropic, Meta Superintelligence Labs, and Microsoft AI.
WHY APPLY
Massive Opportunity: Forbes reported that we could be YC's fastest unicorn, reportedly raising at a $3.2 billion valuation, and we're not slowing down.
Founding Impact: You will own and architect core infrastructure systems that power our platform from the ground up.
Equity & Growth: Competitive salary and meaningful equity. As we scale, you’ll have the opportunity to shape the engineering organization and lead major technical initiatives.
Strong Team: Our founding team has experience from Citadel Securities, Meta, Google, Silver Lake, and Morgan Stanley — work alongside world-class engineers and researchers.
OVERVIEW
As a SWE (Environments), you will design the simulations, data, and evaluations that directly influence how frontier models learn. You'll work hands-on with research teams at top AI labs, experimenting with environment design, piloting novel data creation strategies, diagnosing model failure modes, and developing the metrics that determine whether a model is actually improving. You'll go from hypothesis to live experiment quickly, and your output will feed directly into model training runs at scale. Day to day, you will design environments, tasks, and data that expose meaningful failure modes across domains like finance, code, and enterprise workflows. You will build and refine reward signals for various RL pipelines. You will develop quantitative frameworks for measuring dataset quality, diversity, and downstream impact on alignment and capability. You will partner with lab research teams to translate their training objectives into concrete data and evaluation specifications.
RESPONSIBILITIES
- Construct simulated worlds and explore data shapes that expose meaningful model failure modes across domains like finance, code, and enterprise workflows
- Build and refine evaluation rubrics and reward signals for RLHF and RLVR training pipelines
- Analyze agent-produced trajectories and run experiments to improve different model capabilities
- Develop quantitative frameworks for measuring dataset quality, diversity, and downstream impact on model alignment and capability
- Create and manage both real world & synthetic data pipelines
Partner with lab research teams to translate their training objectives into concrete data and evaluation specifications
- Partner with in-house researchers to run post-training experiments and scale training infrastructure
REQUIRED QUALIFICATIONS
- Ability to design lightweight experiments, move fast, and extract actionable insights from messy results
- Experience with using Docker, or similar containerization tools, to design and monitor systems at scale
- Strong familiarity with common reinforcement learning algorithms and methods, especially with respect to post-training LLMs
PREFERRED QUALIFICATIONS
- Major plus if they've worked for/interned for any RL environment companies in the past or any AI safety or benchmarking orgs like METR, Artificial Analysis, etc.
- Former founders and early engineers at early stage startups are a plus. We want people who can demonstrate they work hard, learn fast, and care deeply about getting the details right.
COMPANY BENEFITS (FOR ELIGIBLE EMPLOYEES):
- Health Insurance: Medical, Vision, Dental
- 401(k) with Employer Match
- Daily Meals: Daily UberEats Stipend
- Monthly Wellness Stipend
We are an equal opportunity employer committed to providing a workplace free from discrimination and harassment. Employment decisions are made without regard to legally protected characteristics under applicable federal, state, or local law.
We comply with applicable pay transparency requirements and provide compensation ranges based on the position, qualifications, experience, and other relevant factors. Reasonable accommodations are available to qualified individuals with disabilities and for sincerely held religious beliefs, as required by law. This job description is intended to describe the general nature and level of work performed and is not an exhaustive list of all duties, responsibilities, qualifications, or working conditions associated with the position. We reserve the right to modify this job description as business needs change.