Overview
At ForUsAll, we’re revolutionizing the U.S. retirement industry with cutting-edge AI technology. Based in San Francisco, our fintech startup is on a mission to provide cost-efficient retirement solutions for small and mid-sized businesses. Founded by industry pioneers who reimagined 401(k) plans for Fortune 500 companies, we’re supported by top-tier venture capitalists and financial tech experts who share our passion for empowering everyday Americans to achieve financial security.
Founded by industry veterans who previously transformed retirement plans for Fortune 500 companies, we’re backed by top venture capital firms and fintech leaders who share our mission to democratize access to modern, diversified retirement portfolios.
This role is highly cross-functional and ideal for someone excited about autonomy, fast-paced iteration, and working on novel problems.
- Design and develop production-grade AI applications using Python and/or JavaScript
- Fine-tune and deploy LLMs, vision models, or other foundation models (e.g., using HuggingFace, OpenAI Fine-tuning APIs, PEFT, DeepSpeed, etc.)
- Build agentic systems with tools like Langchain, AutoGPT, Griptape, LlamaIndex, or Haystack
- Architect and manage vector databases (FAISS, Pinecone, Weaviate, Annoy, HNSWlib) and graph databases (Neo4j, Amazon Neptune, DGL, etc.) to power retrieval-augmented generation and memory-based agents
- Collaborate with the product team to rapidly prototype and ship features powered by generative models
- Lead technical decisions around model selection, performance tuning, and memory persistence
Write clean, modular, and testable code, and contribute to best practices for AI software development
AI/ML Skills (must have 2 or more of the following):
- Hands-on experience building and deploying AI-powered applications
- Strong understanding of fine-tuning techniques: LoRA, adapters, prefix tuning, PEFT, etc.
- Experience with vector databases for semantic search (e.g., FAISS, Pinecone, Weaviate)
- Experience with graph databases and query languages like Cypher or SPARQL
Practical exposure to agentic system design, including tool use, memory, planning, or orchestration (e.g., Langchain, AutoGPT, LlamaIndex)
Technical Stack:
- Proficient in Python (preferred) and/or JavaScript/TypeScript
- Familiarity with ML/DL frameworks like PyTorch, TensorFlow/Keras, JAX
- Comfortable using APIs from OpenAI, Anthropic, Hugging Face, etc.
Experience with cloud deployment (AWS), scalable backend services, or distributed computing tools like Ray