Staff AI Execution Engineer

WHAT WE DO

Nitrogen equips financial advisors with a suite of AI-powered products that showcase the value of their advice so they can attract clients and keep them fearless. Since launching Riskalyze in 2011, we've been on a mission to create what we call Catalyst Moments — those powerful instances when an advisor helps a client go from confused to confident, from fearful to fearless.

Our connected suite brings together Risk Alignment, Investment Research, Income Planning, Tax Intelligence, and Legacy Planning, combining agentic AI with trusted, deterministic analytics to turn complex financial insights into persuasive visuals. The result: clearer conversations, stronger relationships, and advisors who can prove their value in every client meeting.

Trusted by tens of thousands of advisors, backed by an industry-leading NPS of 71, and the first wealthtech company to earn ISO 42001 certification, Nitrogen is built on 13 years of advisor data and half a trillion dollars in assets on platform. We invented the Risk Number®, built on a Nobel Prize-winning academic framework, and we champion the Fearless Investing Movement — because a world empowered to invest fearlessly starts with empowered advisors.

Nitrogen is an equal opportunity employer. We encourage people from underrepresented groups to apply. We are committed to being fair and intentional in our hiring decisions by reviewing every application thoroughly.

THE TEAM

Our Data and Services Team empowers the world to invest fearlessly by by building agentic AI systems and the data-powered services behind them, directing fleets of AI developer tools to ship products that serve advisors and their firms across the wealth management industry.

As a Staff AI Execution Engineer on the Data & Services team, you'll lead how we design, build, and ship AI systems into production across Nucleus and our broader platform. This means architecting agentic workflows, building agent memory and orchestration, and standing up the evaluation frameworks that make agent decisions reliable at scale. You build primarily through agentic AI and you bring real depth in building AI products, pairing both with the data fluency our domain demands. You'll own these systems across their full lifecycle, from design through production, continuously raising what one engineer can deliver.

Staff AI Execution Engineer:

• Advances Nitrogen's AI capabilities with your expertise designing and shipping agentic systems into production use.
• Owns the successful delivery of AI features end-to-end: from agent design and orchestration, through evaluation and hardening, to reliable production systems advisors depend on.
• Builds the foundations that make agents dependable: memory systems, evaluation frameworks, and the patterns that improve agent decisions at scale.
• Sets a high bar for technical productivity through deep, fluent, and consistently advancing use of agentic AI developer tools.
• Pioneers AI-augmented engineering practices on the team, including prompts, harness configurations, and multi-agent orchestration, and shares them so the whole team moves faster.
• Delivers high-quality, production-grade features at a velocity that meaningfully exceeds traditional engineering throughput, while reliably meeting commitments.
• Provides architectural leadership across AI systems and the services and data flows that support them.
• Maintains a deep understanding of what our domain-specific data means to our customers and their product experience.
• Proactively identifies and addresses technical debt and developer experience gaps, advocating for AI-enhanced solutions.
• Mentors and elevates the technical skills of fellow engineers, particularly in building and shipping AI systems.
• Demonstrates a continuous improvement mindset in both personal development and all technical workflows.

WHAT WE DONitrogen equips financial advisors with a suite of AI-powered products that showcase the value of their advice so they can attract clients and keep them fearless. Since launching Riskalyze in 2011, we've been on a mission to create what w...

• Agentic Engineering. You operate at the leading edge of AI-augmented engineering. Tools like Claude Code, Devin, and Cursor are core to how you build, not adjuncts to a traditional workflow. You direct multiple agents in parallel and use them to amplify staff-level judgment rather than replace it.
• AI Systems & Products. You've shipped AI systems into production use, not just prototypes. You build agentic workflows, agent memory, and orchestration, and you know what it takes to make them reliable, observable, and safe for real users.
• Evaluation & Quality at Scale. You deeply understand the evaluation frameworks that improve agent decisions at scale. You design evals, measure agent behavior rigorously, and turn those signals into systems that get measurably better over time.
• AI Tooling & Frameworks. You're fluent with the frameworks that power modern AI systems, including LangChain, LangGraph, GraphQL, and MCP. You evaluate and adopt new tools faster than your peers and can articulate where each one fits.
• AI-Native Productivity. You demonstrably ship more, with higher quality, than traditional throughput allows. You've internalized the disciplines that make agentic tooling pay off: clear specs, tight feedback loops, rigorous review of agent output, and deliberate context engineering.
• Experience. You bring 8+ years of hands-on engineering experience, with substantial depth building production systems and the judgment to know how data engines and pipelines work inside and out.
• Technical Leadership. You are a trusted technical authority that others turn to for solving the most challenging problems and making high-impact decisions. You've given tech talks internally or at conferences. You actively mentor others, reduce knowledge silos, and raise the team's overall capability.
• Data Fluency. You're comfortable with SQL & Python in Snowflake & dbt and the realities of messy real-world data. Experience with CDC, APIs, and services such as DMS, OpenFlow, Kafka, or similar is a strong plus.

The expected compensation range for this role is a $200k-$220k + annual bonus target.

Lesser experience may result in lower compensation and greater experience may result in greater compensation than the stated range.

WHAT WE DO

Nitrogen equips financial advisors with a suite of AI-powered products that showcase the value of their advice so they can attract clients and keep them fearless. Since launching Riskalyze in 2011, we've been on a mission to create what we call Catalyst Moments — those powerful instances when an advisor helps a client go from confused to confident, from fearful to fearless.

Our connected suite brings together Risk Alignment, Investment Research, Income Planning, Tax Intelligence, and Legacy Planning, combining agentic AI with trusted, deterministic analytics to turn complex financial insights into persuasive visuals. The result: clearer conversations, stronger relationships, and advisors who can prove their value in every client meeting.

Trusted by tens of thousands of advisors, backed by an industry-leading NPS of 71, and the first wealthtech company to earn ISO 42001 certification, Nitrogen is built on 13 years of advisor data and half a trillion dollars in assets on platform. We invented the Risk Number®, built on a Nobel Prize-winning academic framework, and we champion the Fearless Investing Movement — because a world empowered to invest fearlessly starts with empowered advisors.

Nitrogen is an equal opportunity employer. We encourage people from underrepresented groups to apply. We are committed to being fair and intentional in our hiring decisions by reviewing every application thoroughly.

THE TEAM

Our Data and Services Team empowers the world to invest fearlessly by by building agentic AI systems and the data-powered services behind them, directing fleets of AI developer tools to ship products that serve advisors and their firms across the wealth management industry.

As a Staff AI Execution Engineer on the Data & Services team, you'll lead how we design, build, and ship AI systems into production across Nucleus and our broader platform. This means architecting agentic workflows, building agent memory and orchestration, and standing up the evaluation frameworks that make agent decisions reliable at scale. You build primarily through agentic AI and you bring real depth in building AI products, pairing both with the data fluency our domain demands. You'll own these systems across their full lifecycle, from design through production, continuously raising what one engineer can deliver.

Staff AI Execution Engineer:

• Advances Nitrogen's AI capabilities with your expertise designing and shipping agentic systems into production use.
• Owns the successful delivery of AI features end-to-end: from agent design and orchestration, through evaluation and hardening, to reliable production systems advisors depend on.
• Builds the foundations that make agents dependable: memory systems, evaluation frameworks, and the patterns that improve agent decisions at scale.
• Sets a high bar for technical productivity through deep, fluent, and consistently advancing use of agentic AI developer tools.
• Pioneers AI-augmented engineering practices on the team, including prompts, harness configurations, and multi-agent orchestration, and shares them so the whole team moves faster.
• Delivers high-quality, production-grade features at a velocity that meaningfully exceeds traditional engineering throughput, while reliably meeting commitments.
• Provides architectural leadership across AI systems and the services and data flows that support them.
• Maintains a deep understanding of what our domain-specific data means to our customers and their product experience.
• Proactively identifies and addresses technical debt and developer experience gaps, advocating for AI-enhanced solutions.
• Mentors and elevates the technical skills of fellow engineers, particularly in building and shipping AI systems.
• Demonstrates a continuous improvement mindset in both personal development and all technical workflows.

WHAT WE DONitrogen equips financial advisors with a suite of AI-powered products that showcase the value of their advice so they can attract clients and keep them fearless. Since launching Riskalyze in 2011, we've been on a mission to create what w...

• Agentic Engineering. You operate at the leading edge of AI-augmented engineering. Tools like Claude Code, Devin, and Cursor are core to how you build, not adjuncts to a traditional workflow. You direct multiple agents in parallel and use them to amplify staff-level judgment rather than replace it.
• AI Systems & Products. You've shipped AI systems into production use, not just prototypes. You build agentic workflows, agent memory, and orchestration, and you know what it takes to make them reliable, observable, and safe for real users.
• Evaluation & Quality at Scale. You deeply understand the evaluation frameworks that improve agent decisions at scale. You design evals, measure agent behavior rigorously, and turn those signals into systems that get measurably better over time.
• AI Tooling & Frameworks. You're fluent with the frameworks that power modern AI systems, including LangChain, LangGraph, GraphQL, and MCP. You evaluate and adopt new tools faster than your peers and can articulate where each one fits.
• AI-Native Productivity. You demonstrably ship more, with higher quality, than traditional throughput allows. You've internalized the disciplines that make agentic tooling pay off: clear specs, tight feedback loops, rigorous review of agent output, and deliberate context engineering.
• Experience. You bring 8+ years of hands-on engineering experience, with substantial depth building production systems and the judgment to know how data engines and pipelines work inside and out.
• Technical Leadership. You are a trusted technical authority that others turn to for solving the most challenging problems and making high-impact decisions. You've given tech talks internally or at conferences. You actively mentor others, reduce knowledge silos, and raise the team's overall capability.
• Data Fluency. You're comfortable with SQL & Python in Snowflake & dbt and the realities of messy real-world data. Experience with CDC, APIs, and services such as DMS, OpenFlow, Kafka, or similar is a strong plus.

The expected compensation range for this role is a $200k-$220k + annual bonus target.

Lesser experience may result in lower compensation and greater experience may result in greater compensation than the stated range.