Staff+ Software Engineer, AI in New York at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff+ Software Engineer, AI based in United States.

This is a high-impact engineering role responsible for the shared AI foundation powering a growing suite of financial planning and analysis capabilities.
You will shape how models are selected, routed, provided with context, connected to tools, and evaluated across the product.
Your work will establish the infrastructure and engineering practices that enable multiple teams to build reliable AI features at scale.
You will also ship agentic experiences end to end, from early prototypes through production optimization and continuous improvement.
Because these systems support financial decision-making, quality, accuracy, observability, and measurable evaluation are critical to the role.
You’ll operate with significant autonomy in a remote-first engineering environment alongside highly technical product and engineering teams.
This is an ideal opportunity for a Staff+ builder who wants to define production AI infrastructure rather than focus primarily on research.

• Own the shared AI foundation used by product engineering teams, including model selection and routing, model proxy infrastructure, context management, and tool design.
• Design and evolve the architecture that allows different AI capabilities and product teams to build on a consistent, reliable foundation.
• Own AI evaluation infrastructure, working with customers and finance-domain experts to define quality standards and translate them into repeatable evaluations.
• Establish evaluation practices that teams can run consistently to measure model and agent performance and identify regressions or opportunities for improvement.
• Build and ship agentic capabilities end to end, from initial proof of concept through production deployment and iterative optimization.
• Apply prompt and context engineering, caching, parallel tool calls, subagent patterns, and other techniques to improve agent performance and efficiency.
• Build observability into agent behavior, enabling teams to profile workflows, identify bottlenecks, diagnose failures, and prioritize improvements using data.
• Monitor developments in agentic AI systems and selectively introduce proven techniques and engineering practices into production workflows.
• Create proof-of-concepts rapidly, validate technical approaches, and turn successful concepts into production-ready v0 implementations.
• Drive adoption of shared systems across teams through strong technical design, usability, reliability, and clear documentation.
• Make pragmatic architectural decisions that balance long-term foundations with the need to ship incrementally.
• Maintain high standards for code quality, correctness, readability, reliability, and maintainability across the systems you build.
• Influence engineering practices beyond your immediate scope and provide technical leadership without relying on formal management authority.
• Communicate complex technical decisions clearly and persuasively with both engineering and non-technical stakeholders.

• Demonstrated experience building and shipping production LLM systems, including areas such as evaluation infrastructure, context management, multi-model routing, or multi-provider architectures.
• Strong practical understanding of what can go wrong in production AI systems, with the ability to explain specific failures, trade-offs, and improvements you have implemented.
• Experience with LLM APIs and agent frameworks, ideally combined with a track record of shipping user-facing AI products.
• Strong understanding of prompt engineering, context design, tool use, agent orchestration, caching, and related techniques for production AI systems.
• Experience designing and implementing evaluation methodologies that establish measurable quality standards for LLM or agentic systems.
• Strong architectural judgment, with the ability to create clear abstractions while avoiding unnecessary complexity.
• A highly pragmatic approach to engineering, with a preference for simple, effective solutions and incremental delivery.
• Strong full-stack engineering fundamentals, including the ability to trace requests across user interfaces, services, APIs, and data stores and make sound technical decisions at each layer.
• Demonstrated high agency, ideally developed through experience as a founder, engineering lead, startup builder, or similarly autonomous engineering role.
• Track record of influencing adoption beyond your immediate team, with other engineers or product teams choosing to use systems you have built.
• Deep commitment to engineering craft, including writing correct, understandable, maintainable, and high-quality code.
• Excellent communication skills, with the ability to be clear, direct, persuasive, and effective across technical and non-technical audiences.
• Experience building complex B2B products, ideally from the ground up.
• Strong product mindset and customer orientation, with the ability to connect technical decisions to real user and business outcomes.
• Motivated by shipping production systems and solving practical engineering problems rather than focusing primarily on academic or exploratory research.
• Comfortable working autonomously in a remote-first environment and collaborating effectively across distributed teams in the Americas.
• Based in the Americas and able to align reasonably with the team's working hours.

• Fully remote work across the Americas.
• Competitive compensation structure with location-based salary ranges and equity participation.
• Flexible working hours designed to support autonomy and effective remote collaboration.
• Unlimited paid time off.
• Regular in-person company retreats and opportunities to build relationships with distributed teammates.
• Company-provided MacBook Pro or Lenovo laptop.
• Health insurance for eligible US and Canadian employees.
• Guideline 401(k) program for eligible US employees.
• Opportunity to work on production AI systems at the intersection of Generative AI, agentic workflows, and financial planning.
• Significant technical ownership and the opportunity to influence architecture and engineering practices across multiple product teams.
• Remote-first environment with a strong focus on autonomy, craftsmanship, pragmatic execution, and high-impact work.
• Equal-opportunity workplace committed to diversity, inclusion,