Founding Engineer, Applied AI Lead

Founding Engineer And Head Of Applied AI

Equi is an investment management firm building institutional-quality alternative investment solutions. We operate a unique business model: in addition to offering Equi-branded funds, we build white-label fund of funds products for some of the top independent multi-family offices and financial advisory firms in the country. We combine deep manager selection expertise with sophisticated portfolio construction to deliver differentiated outcomes for our clients and partners.

The firm is at an inflection point, our AUM is scaling rapidly, we've signed an LOI to launch an additional fund of funds product, and we expect to sign more LOIs in the coming months. We're assembling a small, high-caliber team that can grow with the platform and take on increasing responsibility as we scale.

Equi is seeking a Founding Engineer and Head of Applied AI to serve as the lead builder across the entire company. This is a foundational leadership role where you'll design and build the software solutions that accelerate Equi's growth, working across the investment team, operations, and go-to-market.

You will be the backbone of engineering at Equi, driving projects from ideation through execution across AI-powered systems, customer-facing applications, and internal tools. This role sits at the intersection of AI engineering and application development: you'll build RAG-based intelligence, automate complex investment workflows, and create new customer-facing applications on top of our data infrastructure.

This is a rare opportunity for someone fascinated by sophisticated investment strategies who wants to build technology that powers a rapidly scaling platform. The role will evolve from hands-on building to eventually growing and leading the engineering team, while maintaining our vision of a small, flat organization where everyone stays close to the work.

Equi is a team-first environment where transparency and healthy debate are integral to our success. We operate with a flat structure, ideas win on merit, not seniority, and every team member is expected to contribute to the conversation. We value intellectual honesty, rigorous thinking, and the humility to change your mind when the evidence warrants it.

Our vision for engineering is to keep the team small and flat, where everyone remains involved in building rather than adding layers of management. As the platform scales, there is a clear path to broader responsibility and leadership while staying deeply connected to the technical work.

Lead Builder Across the Company

• Serve as the primary engineer and technical leader, building software solutions that accelerate growth across all teams
• Partner directly with the Investment Team, Operations, and GTM to identify high-impact opportunities for technology and automation
• Exercise significant autonomy, taking ownership of complex projects from conception through post-launch iteration
• Make critical technical decisions and architect scalable solutions for a growing platform

Customer-Facing Applications

• Translate complex user needs and business requirements into well-architected, scalable, maintainable, and user-friendly full-stack applications (Typescript, Next.js, Python, Postgres on GCP)
• Design, implement, and maintain performant and reliable APIs and backend services
• Develop exceptional user experiences for clients and partners

AI Engineering

• Ingest multi-format investment data and parse it into both human- and computer-digestible formats
• Use AI to perform investment analysis and provide recommendations to the human investment team
• Build workflows to automate human actions across the investment process
• Develop RAG-based intelligence systems to power internal and external applications

Team Leadership & Growth

• Act as the backbone of the engineering function, establishing technical direction and best practices
• Lead technical decision-making and architectural design discussions
• Proactively identify and advocate for process improvements and technology adoption
• Eventually grow and lead the engineering team while maintaining hands-on building responsibilities

We are looking for candidates who possess a strong blend of technical depth, product intuition, leadership instincts, and a proactive mindset.

Required

• Experience: 5+ years of professional experience in software development, demonstrating progressive responsibility and impact
• Passion for investing: Experience can't substitute for an innate curiosity and passion for the world of investing. We operate in the depths of it, so you better love it!
• Full-Stack Proficiency: Proven track record of designing, building, deploying, operating, and maintaining complex full-stack web applications in production environments. Strong proficiency in Typescript, Next.js, and Python
• Data & Cloud Foundation: Solid understanding of data pipeline concepts (ETL/ELT) and data warehousing principles
• AI-Driven Engineering: Competent in AI-driven engineering workflows and can use them to deliver effectively; experience building AI-powered applications
• Product Acumen: Demonstrated ability to think critically about product strategy, understand user needs and pain points, and effectively translate them into technical solutions
• Autonomy & Action Orientation: Proven ability to work independently with minimal supervision, navigate ambiguity effectively, and drive projects to completion with a strong sense of ownership and a bias for action
• Collaboration & Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical ideas clearly to both technical and non-technical audiences
• Leadership Potential: Desire and ability to eventually grow and lead a small, high-performing engineering team

Preferred

• Prior experience working in fintech, investment technology, or financial services
• Specific experience designing and scaling large-volume data pipelines or complex distributed systems on GCP
• Experience using containerization technologies like Docker and API middleware like GraphQL
• Familiarity with advanced data modeling techniques
• Experience with RAG systems, LLM integration, or AI agent development
• Defining Our Ideal Candidate: Key Traits in Action
• Beyond technical skills, we seek engineers who embody specific traits that are crucial to our culture and success. These qualities are interconnected and define how we approach building impactful products.

Product-Minded

We value engineers who look beyond the code to understand the bigger picture. A product-minded engineer at Equi is deeply curious about the 'why', why are we building this feature? Who is it for? What problem does it solve? They actively engage with stakeholders across the company, offering thoughtful suggestions, challenging assumptions constructively, and proposing alternative approaches based on their technical insight and understanding of user needs. They excel at evaluating the tradeoffs between engineering effort and product impact, often leveraging data to support their perspectives, ensuring we build not just functional, but truly valuable solutions.

High Autonomy

Trust is fundamental to our engineering culture, and we empower our engineers with significant autonomy. High autonomy at Equi means having the freedom to determine the best way to tackle complex problems and execute tasks within the scope of agreed-upon goals. Engineers who thrive here are self-starters, comfortable navigating ambiguity, proactively seeking information, and taking ownership of their work from end-to-end. This freedom comes paired with accountability; our engineers own their decisions and outcomes, learning and adapting from both successes and setbacks in a psychologically safe environment.

Bias Toward Action

In the fast-paced world of fintech, speed and decisiveness matter. A bias toward action at Equi means valuing progress and learning through doing, rather than getting stalled by over-analysis or the pursuit of unattainable perfection. Engineers with this trait are adept at making calculated decisions, even with incomplete information, understanding that many choices are reversible and that iteration leads to better results. They proactively identify and remove roadblocks, break down large problems into manageable steps, readily experiment, and use feedback to adjust course quickly, ensuring we continuously deliver value to our customers. This proactive approach, enabled by autonomy and guided by a product mindset, is key to our innovation cycle.