Staff Back End Engineer, Altruist

• We're looking for an AI-native Staff Software Engineer who combines creative thinking with business acumen
• 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 take responsibility for business outcomes, carry changes through production, and support the systems you build
• Communication - You listen carefully, explain complex ideas clearly, and work effectively with technical and nontechnical partners
• Resilience and humility - You navigate uncertainty, learn from setbacks, and adapt your approach when evidence or a different perspective calls for it
• Creative problem solving - You question assumptions, identify root causes, and develop practical solutions to difficult problems
• Education - B.A. or B.S. in Computer Science, or equivalent practical experience
• Snowflake, Airflow, or dbt in production environments
• Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Altruist we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role, but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles

Desirable

• 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
• 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