Applied AI Engineer

Recruiting From Scratch•San Francisco, NY

2d•Hybrid

About The Position

Our client is building AI-powered software and infrastructure that helps sophisticated institutional investors become AI-native. The company develops intelligent platforms that combine agentic AI, LLMs, data orchestration, and financial workflows to help hedge funds and asset managers automate complex research, analytics, and investment processes. The business has reached more than $10M in ARR without external venture funding, demonstrating strong product-market fit and a highly capital-efficient operating model. The engineering team operates with a strong R&D mindset, continuously evaluating new AI technologies and incorporating them into production systems. Engineers have significant ownership over architecture, product direction, and implementation. As an Applied AI Engineer, you'll build AI-powered applications and infrastructure directly used by investment teams, working across agentic workflows, MCP-connected systems, LLM applications, financial data pipelines, and full-stack product development. This is an opportunity for a strong software engineer who wants to work at the intersection of modern AI and institutional finance while owning projects from 0-to-1.

Requirements

3–8 years of experience as an Applied AI Engineer, Software Engineer, Full-Stack Engineer, or related technical role
Experience building user-facing AI products or features from 0-to-1
Experience building production applications using modern AI technologies
Hands-on experience with LLM-powered applications
Experience building agentic AI products or workflows
Experience working with AI APIs and modern AI tooling
Strong full-stack software engineering experience
Experience building customer-facing or user-facing applications
Experience operating effectively in highly autonomous environments
Experience translating ambiguous problems into working software
Experience shipping production software on compressed timelines
Experience collaborating directly with users or customers
Strong product engineering mindset
Strong Python engineering skills
Python API development experience
Experience with FastAPI, Flask, Django, or similar frameworks
Experience building and integrating REST APIs
Hands-on experience with LLM APIs
Experience with agentic AI frameworks
Strong understanding of the agentic loop underlying modern AI frameworks
Experience with prompt engineering
Experience building AI-powered user-facing applications
Strong React experience
Strong JavaScript/TypeScript fundamentals preferred
Strong SQL experience
Experience building ETL and data pipelines
Experience working with structured and unstructured data
Experience with Pandas or Polars
Experience with data orchestration and workflow systems
Experience deploying applications using Kubernetes
Experience working with Azure or comparable cloud infrastructure
Strong API architecture and integration skills
Strong software engineering fundamentals
Ability to design scalable backend services
Ability to troubleshoot complex production systems
Ability to rapidly learn and adopt emerging AI technologies
Ability to evaluate AI tooling based on practical product requirements
Strong understanding of application architecture
Ability to build reliable production systems using existing AI infrastructure
Strong debugging and problem-solving skills
Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field preferred
Strong computer science and software engineering fundamentals
Equivalent practical engineering experience accepted
Exceptional ownership and execution ability
Highly autonomous working style
Strong builder mentality
Comfortable working in unstructured environments
Strong first-principles problem-solving ability
Comfortable solving loosely defined problems
Strong product intuition
Excellent technical communication skills
Strong customer empathy
Comfortable working directly with investment teams
Strong curiosity around emerging AI technologies
Genuine interest in how AI is transforming software
Comfortable moving quickly from idea to production
Strong bias toward action
Comfortable making technical decisions independently
Strong ability to iterate based on user feedback
Comfortable working across backend, frontend, data, and AI systems
Strong attention to engineering quality
Comfortable building 0-to-1 products
Comfortable learning unfamiliar technologies quickly
Strong collaboration skills
Low-ego working style
Comfortable operating with limited structure
Strong sense of urgency
Comfortable working in a lean engineering organization
Interested in working directly with sophisticated financial customers
Comfortable working in-person in New York 4 days/week
Interested in building software for institutional investors

Nice To Haves

Experience working in startup or high-growth environments preferred
Strong interest in institutional finance, hedge funds, asset management, or quantitative investing
Experience with MCP servers and MCP-connected tools preferred
Experience with frameworks such as LangChain, LangGraph, Claude Code, OpenClaw, OpenCode, or similar tooling
Strong JavaScript/TypeScript fundamentals preferred
Experience with financial or time-series data preferred

Responsibilities

Build AI-powered features directly into client-facing financial platforms
Develop LLM-powered research intelligence and automation tools
Build agentic workflows that automate complex investment and research processes
Design and implement AI orchestration systems and agent pipelines
Build MCP-connected tools and data sources for intelligent applications
Build internal and client-facing AI infrastructure
Build AI observability systems and agent health monitoring capabilities
Develop expert skills and reusable AI tooling for client implementations
Build command-line tools and MCP servers that extend AI capabilities
Design data orchestration systems connecting AI agents to financial datasets
Build full-stack applications tailored to institutional investment workflows
Develop backend APIs using Python and frameworks such as FastAPI
Build responsive front-end interfaces using React
Develop natural-language interfaces for complex financial datasets
Build automated summarization and research intelligence systems
Develop AI-powered workflow automation for hedge funds and asset managers
Build ETL pipelines handling financial market data
Work with positions, securities, risk metrics, and research signals
Implement financial analytics and data processing workflows
Work with time-series data and quantitative financial calculations
Use tools such as Pandas and Polars for financial data analysis
Deploy and operate applications within client environments
Work with Kubernetes to deploy and maintain production applications
Integrate LLM APIs and modern AI infrastructure into production systems
Evaluate emerging AI frameworks and determine where they can create meaningful product value
Build applications using modern agentic AI frameworks
Work directly with investment teams to understand complex workflows
Translate loosely defined financial problems into production software
Ship customized platforms on compressed timelines
Iterate quickly based on direct customer feedback
Make architectural decisions across the AI and application stack
Balance building from scratch with leveraging proven infrastructure
Own projects from initial concept through production deployment
Build software that compresses complex analyst workflows from weeks into seconds
Continuously improve AI-powered applications based on real-world usage
Establish reusable engineering patterns for AI implementations
Help shape the company's long-term AI application and infrastructure strategy

Benefits

Competitive equity package
Opportunity to join a bootstrapped company with $10M+ ARR
Opportunity to work on production AI applications used by sophisticated financial institutions
High ownership over AI-powered products and infrastructure
Direct exposure to hedge funds and institutional investment teams
Opportunity to build 0-to-1 AI products
Exposure to cutting-edge agentic AI, LLM, and MCP technologies
Opportunity to work across AI infrastructure, backend, frontend, and data systems
Strong R&D-oriented engineering culture
High autonomy and limited bureaucracy
Direct impact on product architecture and technical direction
Opportunity to work alongside engineers with backgrounds in leading financial institutions
Hybrid work environment in New York City
H-1B / OPT and other visa transfer support