Altruist is transforming the multi-trillion dollar wealth management industry by building an AI platform for wealth professionals. We partner with financial advisors nationwide, empowering them to grow, optimize time and resources, and deliver superior outcomes for their clients. We're looking for exceptional talent to help us achieve our mission of making financial advice better, more affordable, and accessible to all. If you're passionate about challenging the status quo and want to do the most important work of your life, we'd love to meet you! But first, our values Kindness - Kindness doesn’t just equal niceness. We listen to understand. We embrace, and encourage healthy debate and diverse perspectives. We approach conflict openly, honestly, and respectfully. Brilliance - Humility is the skill we’re most proud of and possessing a growth mindset is always top of mind. We take ownership in everything we touch; regularly using our unique superpowers to reach a common goal as a team. We succeed and fail as one. Grit - When challenges arise, we stay laser focused on achieving our mission and finding a way forward, even when it’s hard. We are nimble and maintain a sense of urgency, swiftly adapting to change and overcoming obstacles. The opportunity Altruist is in the midst of an exceptional growth phase and we’re excited to hire a Staff Back End Engineer focused on building innovative Generative AI products for Altruist’s advisors in the newly formed AI Labs team. Title can be flexible depending on experience. Your impact Act as a leader and steward of engineering best practices, helping to mentor other engineers and develop impactful solutions. Analyze and solve complex problems spanning multiple user personas and workflows Focus on building and scaling services and user facing web applications Build customer centric scalable and performant AI-driven applications and features Develop and maintain scalable data pipelines and ELT processes Build new data integrations based on established requirements Perform data analysis to investigate and resolve data issues
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
101-250 employees