Jobs at EVB

Remote contractor role for a US-licensed corporate and M&A lawyer supporting legal data annotation for AI training. Responsibilities include developing and reviewing tasks involving M&A structuring, governance, due diligence, commercial contracts, and securities law; evaluating corporate documents; providing written feedback; resolving legal ambiguities; creating annotation guidelines and quality checks; and monitoring US legal developments.

Reviews, debugs, annotates, and evaluates code and technical documentation across multiple programming languages. The role involves assessing AI-generated software solutions, simulating developer workflows, troubleshooting codebases, comparing responses to complex prompts, and documenting actionable feedback to improve AI systems. Work is performed independently and remotely, with strong emphasis on technical accuracy, clear communication, and careful analysis of multi-step coding discussions.

Design realistic, multi-step business operations benchmark tasks for evaluating AI systems. Responsibilities include creating workflows, reports, process documentation, spreadsheets, reference materials, and objective grading criteria. Candidates must identify ambiguous or ungradable tasks and deliver approved work on schedule. The role requires substantial hands-on operations experience, structured standards such as SOPs or QA checklists, strong Excel skills, and strong written and spoken English.

Design realistic, multi-step HR and people operations benchmark tasks for AI evaluation. Develop supporting materials such as policies, payroll reports, headcount data, and employment agreements; define objective grading criteria; identify ambiguity; and deliver approved tasks on schedule. Work requires substantial hands-on experience in payroll, workforce planning, HR policy, or employee lifecycle operations, plus strong written and spoken English.

Build and improve AI recruiting agents using modern LLMs, Python backend services, APIs, prompts, RAG, workflows, and agent orchestration. Evaluate model performance, experiment with AI technologies, collaborate with product and engineering teams, and deploy scalable production systems. The role requires Python, LLM and AI API experience, familiarity with agent frameworks and FastAPI, and cloud platform knowledge. Production AI product experience, model evaluation, tool calling, prompt engineering, and open-source contributions are preferred.

Build realistic coding tasks involving feature implementation and bug fixes for AI systems. Develop deterministic verifiers that accept valid solutions and reject invalid ones. Apply backend expertise in scalable services and APIs, debugging, performance optimization, automated testing, code review, refactoring, and complex feature development. The role is remote, contractor-based, flexible, and output-compensated, with work expected to begin shortly after onboarding.

Build and deploy AI systems for leading labs and enterprise partners. Responsibilities include designing data intelligence platforms, ML and evaluation pipelines, taxonomies, labeling workflows, LLM applications, multi-agent and RAG systems, inference infrastructure, and human-in-the-loop workflows. The engineer will translate ambiguous research needs into production systems, manage full technical lifecycles, and collaborate directly with researchers, founders, and strategic partners.

Create reinforcement learning environments and golden reference solutions for AI software-engineering tasks. Develop code samples, debug complex defects, implement features, refactor legacy systems, optimize performance, document technical reasoning, and review peer submissions. Work may involve Python, Java, Rust, Go, C++, or TypeScript. The role is remote, part-time contract work with output-based compensation and rapid onboarding.