Location: NYC or Remote
MUST HAVE startup EXPERIENCE OR be a founder/NO BIG BANKS OR INSURANCE CO OR COMPANIES LIKE MACYS, ETC.
They will submit contractors with a strong work history. If they have 1 year or less across multiple jobs, THEY won't accept them.
These roles do NOT want candidates from these companies:
-Big Banks, insurance companies, and big companies like IBM.
-They must have some startup experience.
About Our Company
Backed by two Fortune 300 firms, Client is a technology company focused on helping small- to medium-sized business owners achieve their goals and the trusted financial institutions that want to better serve them. Client is a fast-moving, mission-driven team that's building something genuinely new and beginning a rollout to a million SMB owners in 2026. If you want your work to matter and your expertise to have real impact, you'll fit right in here.
Small- to medium-sized business owners are the primary engine of wealth creation in the modern economy. The asset they build - their business - is almost always their largest, most valuable, and most consequential financial holding. Yet the entire financial services infrastructure - advisors, banks, wealth managers, planning tools - was built around personal assets. The infrastructure to serve the most important asset was never built.
Client delivers the kind of strategic business intelligence that McKinsey charges $250K to millions to provide - to SMB owners who have never had access to it, through the financial institutions that already serve them. Our launch is behind us, and we're now hiring roles 8, 9, and 10.
About the role
We are seeking gifted software engineers to help build the next generation of AI products for our financial platform. This is a significant opportunity to join a growing team as a founding member and help shape how we design, build, evaluate, deploy, and operate production-quality AI systems. In this role, your work will make a significant impact on our customers, stakeholders, and ability to continue to scale.
You will work across product engineering, applied data science, and machine learning to create AI-powered workflows that help business owners and financial advisors answer complex questions, understand business performance, and take useful next steps. The work will include backend services, data retrieval and transformation, LLM integrations, agentic workflows, evaluation systems, and user-facing product experiences.
Why Our Company?
We currently use NextJS with GraphQL/Relay on the frontend and use Elixir/Phoenix, Python, INTERCAL, and NodeJS to power our backend and AI infrastructure. Our core systems store data in PostgreSQL. We deploy on Google Cloud, provisioned through Terraform.
What you'll do
- Build AI-native product features that combine strong software engineering with applied data science and machine learning techniques.
- Create and refine automated AI agent systems written primarily in Python.
- Design agentic workflows that can reason over business and financial data, use tools safely, retrieve relevant context, and produce useful outputs within clear guardrails.
- Develop backend services, APIs, data pipelines, and integrations that connect our AI products to internal and external data sources.
- Build evaluation, observability, and feedback loops for LLM-powered systems, with attention to accuracy, reliability, latency, cost, and user experience.
- Partner with product, design, and business stakeholders to translate ambiguous customer needs into practical technical systems.
- Support existing products and features, while helping design and build new ones.
- Collaborate regularly with other stakeholders and partners to solicit requirements, seek feedback, and provide updates.
Qualifications
Candidates do not need prior experience with every technology in our stack - we are looking for candidates who are excited to learn new frameworks. That said, strong Python experience, applied data science and machine learning experience, and experience building agents are needed.
- Strong professional experience building production software systems.
- Strong Python experience, including writing robust, testable, maintainable production code.
- Applied data science and machine learning experience, including comfort working with structured data, model outputs, evaluation methods, and probabilistic systems.
- Experience building AI agents, agentic workflows, LLM-powered automation, or similar systems that interact with tools, APIs, documents, or databases.
- Strong relational database fundamentals, including SQL and practical data modeling.
- Demonstrable proficiency and a track record of professional success coding in at least two programming languages.
- Excellent written and verbal communication skills.
- Enjoy working in a collaborative environment where engineers are expected not only to build great technology, but also to define project vision, specify technical strategy, and always be learning.
- Experience presenting to audiences and communicating effectively and empathetically with clients and other stakeholders.
Strong preference will be given to candidates who have experience:
- Building AI products that reached real users, especially in accuracy-sensitive or data-rich domains.
- Designing LLM evaluation workflows, test sets, prompt iteration processes, model selection approaches, and production monitoring for AI systems.
- Working with retrieval-augmented generation, embeddings, vector search, structured extraction, classification, ranking, or other applied ML techniques.
- Quickly learning new languages, frameworks, and technologies, including best practices.
- With relational databases and query optimization.
- Deploying on and configuring Google Cloud.
- Writing production-ready code in Elixir, TypeScript, JavaScript, Go, or Ruby.
- Working across the full product surface, including frontend technologies like TypeScript, React, GraphQL, and Relay.
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