Staff Back End Engineer, Data

Altruist · San Francisco, CA

  • Senior
  • Full-time
  • $203,000 – $275,000
  • Posted 2026-10-08
  • Confirmed live on 13 October 2026

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Job description

About Altruist

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

We're looking for an AI-native Staff Software Engineer who combines creative thinking with business acumen. You’ll shape the technical direction of our data and AI platforms and stay hands-on in building systems that help financial advisors deliver exceptional client service.

As a senior individual contributor, you’ll lead complex initiatives across teams, turn ambiguous business needs into practical technical plans, and build frameworks that other engineers can use. You’ll own outcomes from design through production, balancing delivery speed with reliability, security, and cost.

Your impact

• Set technical direction for scalable data pipelines and data serving platforms, aligning architecture and investment decisions with business priorities.

• Design and build high-performance systems that manage the full lifecycle of financial data, from ingestion and transformation to serving and consumption.

• Create shared frameworks and platforms that establish AI as a core company capability, including reliable ways for AI applications and agents to access trusted data.

• Identify opportunities to improve advisor experiences and internal workflows with AI. Partner with product and engineering teams to define success, validate approaches, and deliver measurable results.

• Lead initiatives spanning multiple teams, clarify technical tradeoffs and dependencies, and guide delivery from initial design through rollout and ongoing operation.

• Establish standards for data quality, observability, and recovery. Partner with Security to protect sensitive data and make access controls part of system design.

• Improve query performance, platform reliability, and infrastructure efficiency. Resolve complex production issues and address their underlying causes.

• Advance the effective use of AI throughout the software development lifecycle while maintaining accountability for correctness, security, and maintainability.

• Mentor engineers, lead design reviews, and raise engineering standards through clear technical guidance and hands-on contributions.

What you bring

• Experience - 8+ years of software engineering experience, with a track record of leading complex platform or distributed systems initiatives and delivering results across teams.

• Hands-on engineering - Strong proficiency in Python or Java, strong SQL skills, and the ability to design, build, debug, and operate production systems.

• Data platforms - Deep experience with databases, data warehouses, ETL or ELT pipelines, and mature data processes at scale. You understand data modeling, query optimization, and the tradeoffs between batch and real-time processing.

• Distributed processing - Experience with large-scale offline processing and batch pipelines using Spark or similar frameworks, including failure recovery and performance tuning.

• Cloud infrastructure - Experience designing and operating cloud services, especially on AWS, with working knowledge of Kubernetes, deployment practices, and observability.

• AI fluency - Proficiency with AI-assisted development tools such as Cursor or Claude Code, sound judgment about their limitations, and the ability to help others use them effectively. You can identify practical applications of AI and evaluate whether they solve the business problem.

• Technical leadership - Experience setting architectural direction, writing clear technical proposals, building alignment across teams, and mentoring engineers without relying on formal authority.

• Business judgment - The ability to turn ambiguous needs into clear priorities, make pragmatic build-versus-buy decisions, and balance immediate delivery with long-term platform needs.

• Ownership - You

Prepare for the interview

Nothing collected for this employer yet. The Blind 75 is what technical screens draw from; practise it here, with a coach, in Java or Python.

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