Role Description Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves: - Design tasks where the easy path is the unsafe one, and write the tests that catch it: - Build realistic developer environments — a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history. - Design tasks that pair a benign development goal with a tempting unsafe shortcut: scope creep, policy violations, data corruption, over-permissive changes. - Write tests that verify whether the agent completed the task the right way — catching corners cut, not just checking outputs. - Iterate on tasks and tests based on QA feedback — review agent solutions, analyze failures, and refine until the evaluation is fair and robust. What this is NOT: - Not data labeling; - Not prompt engineering; - Not cybersecurity or red-teaming — there is no attacker in the scenario. Cybersecurity experience is a nice-to-have but not a requirement. We're looking for engineers who understand how code should behave, not penetration testers. Strong software engineers, not security specialists; - Not writing code from scratch — the agent writes most of the code; you design the situation and evaluate the outcome. Qualifications - 4–5+ years in software development; - Core stack: Python, JavaScript/TypeScript; - Strong test design skills — functional and integration tests that separate safe from unsafe completion, not just correct from incorrect; - Hands-on experience with coding agents (Claude Code, GitHub Copilot CLI, Codex, or similar); - Familiarity with GitHub PRs and CI workflows as a user; - Stack breadth is welcome, not a filter. Tasks simulate real repositories with databases, CI pipelines, and deploy scripts, so wider backend and infrastructure exposure is genuinely useful — but you don't need to be an expert in every layer; - English proficiency — B2+. Requirements - Creating a task that genuinely challenges the best models is non-trivial. - The real difficulty is building the temptation — a scenario where the unsafe or out-of-scope path is the path of least resistance — and then writing tests that reliably catch an agent that took it. - Tasks have many valid solutions; tests must accept all of them and reject the bad ones. Project time expectations - For this project, tasks are estimated to require around 20-25 hours per week during active phases, based on project requirements. - This is an estimate, not a guaranteed workload, and applies only while the project is active. - Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted. Compensation - On this project, contributors can earn up to $60 per hour equivalent, depending on their level and pace of contribution. - Compensation varies across projects depending on scope, complexity, and required expertise. - Please note that other projects on the platform may offer different earning levels based on their requirements.

• Embed with client teams to understand how work actually happens, shadowing operators and mapping processes that live in people's heads, spreadsheets, and a dozen disconnected tools • Break down complex business processes into agentic workflows: decompose a goal into steps, decide what an agent automates versus where a human stays in the loop, and design the tool-use and decision logic to match • Build production-grade agentic workflows using frameworks like LangGraph and LangChain, including tool calling, memory, routing, retries, and clean failure recovery • Build integrations to the data and operational systems that workflows depend on: CRMs, ERPs, ticketing systems, data warehouses, internal APIs, and document stores, handling auth, rate limits, and reliability • Enable core platform capabilities that the whole engagement reuses: retrieval over client documents, structured output and function calling, prompt versioning, logging, and observability • Design evaluation and guardrails that make a workflow trustworthy in an enterprise setting: task-specific evals, regression checks, PII handling, and human review steps where the stakes demand them • Run working sessions and demos that keep business stakeholders bought in, translating technical tradeoffs into clear decisions about cost, risk, and timeline • Document what you build and hand it over cleanly, so client teams can operate and extend the workflows after the engagement • Bring patterns back to BOD, turning what worked on one engagement into reusable building blocks for the next

Role Description We're looking for an Enterprise Finance Engineer — someone who can design and implement AI-powered finance systems for our largest and most complex customers. This role sits at the intersection of Finance, Accounting, Systems, Automation, Integrations, and AI. You'll work directly with CFOs, Finance Directors, Controllers, IT teams, and finance teams to redesign finance operations through AI, automation, and system integrations. You'll own a small number of large, strategic customers end-to-end — from understanding business processes to designing scalable solutions and continuously improving them as the business evolves. This isn't a role for someone who wants repeatable implementations or well-defined requirements. Every customer is different. You'll navigate ambiguity, work with demanding stakeholders, and solve unique technical problems without predefined playbooks. If that energizes you, we'd love to meet you. Responsibilities - Design and implement AI-powered finance systems for enterprise customers - Lead discovery sessions to understand finance processes and identify automation opportunities - Build workflows for reporting, forecasting, financial controls, reconciliations, and planning - Design integrations across ERP, accounting, CRM, payment, BI, and data platforms - Translate finance requirements into scalable workflows, automations, and system architecture - Build AI agents, validation logic, and automation frameworks that reduce manual work - Partner with Engineering on APIs, integrations, and workflow orchestration - Coordinate across Engineering, Product, and Customer Success as the trusted technical partner for your customers - Continuously improve customer solutions as business needs evolve Qualifications - 10+ years implementing finance systems, automations, or enterprise finance operations - 1+ year building AI-powered automations, agents, workflows, or internal AI tools - Hands-on experience with APIs, system integrations, automation platforms, and data warehouses - Experience working with enterprise or multi-entity organizations (multiple stakeholders, legacy systems, changing requirements, long implementation cycles) - Proven experience leading implementation projects end-to-end — discovery, solution design, rollout, training, and support - Fluent English - Strong understanding of finance and accounting processes, including financial close, reporting, FP&A, revenue, AP/AR, and financial controls - Ability to understand how financial data flows across systems and departments - Experience with ERP, accounting, or billing systems - Proven impact in numbers: hours saved, manual work reduced, faster reporting, or fewer errors - Excellent communication skills and experience working directly with senior finance stakeholders - Strong systems thinking — the ability to see the bigger picture and break complex finance processes into scalable, maintainable, reusable solutions - Ownership: taking full responsibility from problem discovery through implementation and post-launch optimization - Learning agility: quickly mastering new AI tools, technologies, and approaches - Strong problem-solving under ambiguity, with the judgment to make trade-offs and prioritize - Strong drive to eliminate repetitive manual work - Proactivity and a high level of responsibility - Ability to work in a fast-paced environment Requirements - Python or other scripting experience - SQL and the ability to retrieve and validate financial data independently - Experience with tools like NetSuite, QuickBooks, Xero, Stripe, Salesforce, HubSpot, Zuora, BigQuery, Snowflake, PostgreSQL, Looker, Power BI, Tableau, Zapier, Make, n8n, or Workato - Understanding of enterprise architecture — security, scalability, governance, and integration patterns - Experience working with US-based clients or startups Benefits - Build the future of finance work — design AI-native finance operations, not just maintain them - Rapid skills improvement (you'll work with multiple client businesses with different models and challenges) - Growth opportunities according to our seniority grading (it comes with a compensation increase) - Flexible schedule and time-off policy - 18 days of paid vacation per year, paid sick leaves

• Design, configure, develop, and support solutions using Microsoft Dynamics 365 • Build and maintain Power Automate workflows for business process automation and system integration • Work with Dataverse and the wider Microsoft Power Platform to deliver maintainable business applications • Troubleshoot Dynamics 365, Dataverse, and Power Automate issues, including workflow failures and data inconsistencies • Contribute to solution quality, maintainability, monitoring, and operational support • Work directly with business and technical stakeholders to understand requirements, clarify priorities, and propose suitable solutions • Translate business requirements into clear technical designs and implementation plans • Explain technical concepts, constraints, risks, and trade-offs clearly to non-technical audiences • Take ownership of work from requirements gathering through implementation, release, and support • Produce clear technical documentation and communicate progress, risks, and decisions effectively • Collaborate with engineering, product, operations, and support teams throughout the delivery lifecycle • Support integrations between Dynamics 365 and internal or third-party systems • Work with APIs, connectors, and connected business applications • Assist with investigation and delivery of integration components where required • Engage specialist application or .NET engineers where deeper middleware expertise is needed