This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role offers an exciting opportunity to lead the development of next-generation AI systems at scale, transforming how millions of users interact with intelligent financial services. As Lead Software Engineer, you will: - Define and implement AI architectures. - Orchestrate agentic workflows. - Integrate LLMs and Generative AI into production-grade systems. - Collaborate closely with product, design, and data teams to ensure AI features deliver safe, personalized, and high-impact experiences. - Provide technical leadership and hands-on engineering. - Shape AI standards, mentor teams, and influence strategic decisions across multiple markets. - Work remotely from the U.S., with occasional travel to build relationships and align on initiatives. Accountabilities: - Lead the AI architecture and technical roadmap, ensuring LLM integrations are scalable, reliable, and cost-effective. - Design and implement agentic workflows and retrieval-augmented generation (RAG) patterns that enhance customer experiences. - Establish and promote engineering standards for AI development, creating reusable components and best practices. - Collaborate across teams, including Product, Design, and Data Science, to embed AI capabilities across web, mobile, and internal tools. - Define and monitor quality, safety, and evaluation practices for AI outputs, ensuring human-in-the-loop integrity. - Mentor engineers and participate in hiring, fostering high performance and knowledge sharing within technical guilds and AI learning programs. - Balance short-term delivery with platform stability, making informed strategic trade-offs on model selection, system complexity, and operational efficiency. Qualifications - Proven experience as a technical leader delivering large-scale software systems in production environments. - Hands-on experience implementing LLMs, Generative AI, or RAG workflows at scale. - Proficiency in full-stack development, including maintainable codebases and API design bridging AI inference layers with user-facing surfaces. - Strong problem-solving skills, with experience managing complex, ambiguous projects across multiple teams and stakeholders. - Strategic mindset linking technical AI initiatives to business outcomes such as efficiency, customer acquisition, and product innovation. - Experience mentoring and scaling engineering teams, fostering collaboration and high performance. - Bonus: familiarity with PyTorch, TensorFlow, Python AI toolchains, cloud-native infrastructure (AWS/Azure), mobile frameworks like Flutter, and regulated industry standards (FinTech, Responsible AI). - Experience in global-scale products serving diverse markets and multiple languages is a plus. Requirements - Proven experience as a technical leader delivering large-scale software systems in production environments. - Hands-on experience implementing LLMs, Generative AI, or RAG workflows at scale. - Proficiency in full-stack development, including maintainable codebases and API design bridging AI inference layers with user-facing surfaces. - Strong problem-solving skills, with experience managing complex, ambiguous projects across multiple teams and stakeholders. - Strategic mindset linking technical AI initiatives to business outcomes such as efficiency, customer acquisition, and product innovation. - Experience mentoring and scaling engineering teams, fostering collaboration and high performance. - Bonus: familiarity with PyTorch, TensorFlow, Python AI toolchains, cloud-native infrastructure (AWS/Azure), mobile frameworks like Flutter, and regulated industry standards (FinTech, Responsible AI). - Experience in global-scale products serving diverse markets and multiple languages is a plus. Benefits - Remote-first work with quarterly travel to collaborate with colleagues in strategic hubs. - Top-tier medical, dental, and vision insurance. - Generous paid time off, company holidays, and supportive work-life balance culture. - Life Insurance and AD&D coverage. - Extended maternity and paternity leave. - Access to internal learning programs and language courses for professional development. - Mental health and wellness support programs. - Retirement and savings plans including 401K, HSA, and FSA options.

• Lead engineering teams that deliver AI-powered product and platform capabilities with clear impact. Reduce administrative toil, improve family responsiveness, streamline enrollment, and surface better insights for operators. • Build software that not only records information, but also recommends next steps, completes routine work, and automates meaningful parts of our customers’ day-to-day operations. • Use AI agents, automation, and modern tooling to improve how teams build, test, ship, and support software, increasing velocity and freeing up more capacity for high-value work. • Operate an AI hybrid engineering workforce in which engineers and agents work together effectively, with the tooling, guardrails, governance, evaluation, and observability required. • Apply the same AI-native mindset to internal functions like customer support and onboarding, helping the company become faster, more responsive, and more efficient as it scales. • Drive continuous improvements in quality, reliability, and security by using agentic workflows to catch issues earlier, reduce operational burden, and improve the product every week. • Hire and scale exceptional AI-native engineering talent, building a lean, high-performing organization with high standards, strong ownership, and a bias for action. • Make strong build-versus-buy, architecture, and platform decisions that balance short-term speed with long-term leverage and differentiation.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous energy engineering problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for energy engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Energy Engineering or related fields, e.g. Electrical Engineering, Power Systems Engineering, Renewable Energy Engineering, Electronics etc. - 3+ years of professional energy engineering experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PE, CEng, EMP, CEM) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 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. Payment - Paid contributions, with rates up to $50/hour*  - Fixed project rate or individual rates, depending on the project - Some projects include incentive payments *Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous energy engineering problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for energy engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Energy Engineering or related fields, e.g. Electrical Engineering, Power Systems Engineering, Renewable Energy Engineering, Electronics etc. - 3+ years of professional energy engineering experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PE, CEng, EMP, CEM) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 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. Payment - Paid contributions, with rates up to $50/hour*  - Fixed project rate or individual rates, depending on the project - Some projects include incentive payments *Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.