Software Engineer - AI
Role details
Job location
Tech stack
Job description
We are looking for a Software Engineer - AI to design, build, and ship the intelligent systems at the core of our WealthOS platform. You will work across the full AI stack: from data ingestion and embeddings to LLM orchestration, agentic workflows, and user-facing features that put AI directly into the hands of wealth management professionals.
This is a hands-on engineering role with high autonomy. You will collaborate closely with the CTO and a small founding engineering team, making meaningful architectural decisions and seeing your work in production quickly.
What You Will Do
- Design and implement production AI/ML systems including LLM-powered features, retrieval-augmented generation (RAG) pipelines, and agentic workflows for the WealthOS platform.
- Build and optimize data pipelines that ingest, transform, and index financial data (portfolio holdings, market data, client records) for use by AI models.
- Develop and maintain vector search infrastructure using tools like Pinecone, Weaviate, pgvector, or similar for semantic retrieval and knowledge bases.
- Integrate with LLM providers (OpenAI, Anthropic, open-source models) and build prompt engineering frameworks, guardrails, and evaluation harnesses.
- Implement agentic AI patterns: multi-step reasoning, tool use, function calling, and autonomous task execution tailored to wealth management workflows.
- Build robust backend services and APIs (Python, TypeScript, or Go) that serve AI capabilities to front-end applications reliably and at low latency.
- Contribute to infrastructure and DevOps: CI/CD pipelines, containerization, cloud deployment (AWS/GCP), monitoring, and observability for AI systems.
- Participate in code reviews, architectural discussions, and technical planning, helping to establish engineering best practices from the ground up.
- Stay current with the rapidly evolving AI landscape and evaluate new models, frameworks, and techniques for potential adoption.
Requirements
- 3+ years of software engineering experience, with at least 1 year building AI/ML-powered features or applications in a production environment.
- Strong programming skills in Python, with experience in frameworks like FastAPI, LangChain, LlamaIndex, or similar AI/LLM tooling.
- Hands-on experience with large language models: prompt engineering, fine-tuning, embeddings, RAG architectures, and evaluation methodologies.
- Solid understanding of software engineering fundamentals: data structures, algorithms, system design, API design, and testing practices.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerized deployments (Docker, Kubernetes).
- Comfort working with databases (PostgreSQL, Redis) and vector stores for hybrid search and retrieval.
- Strong collaborative instincts: you communicate clearly, give and receive feedback well, and enjoy working in a small, fast-moving team.
- Intellectual curiosity and a genuine enthusiasm for AI: you follow the latest research, experiment with new tools, and bring ideas to the table.
Nice to Have
- Experience with financial data, wealth management platforms, or fintech applications.
- Familiarity with agentic AI frameworks (AutoGen, CrewAI, custom agent architectures) and tool-use patterns.
- Experience with model fine-tuning, RLHF, or training custom models on domain-specific data.
- Contributions to open-source AI/ML projects or published research in NLP, information retrieval, or related fields.
- Experience with frontend development (React, TypeScript) for building AI-powered user interfaces.
- MS or PhD in Computer Science, Machine Learning, or a related field.
Our Tech Stack
AI / LLMs
OpenAI, Anthropic Claude, open-source models, LangChain, LlamaIndex
Backend
Python (FastAPI), TypeScript (Node.js)
Data & Search
PostgreSQL, Redis, Pinecone / pgvector
Infrastructure
AWS / GCP, Docker, Terraform, GitHub Actions
Monitoring
Datadog, LangSmith, custom evaluation pipelines
Benefits & conditions
Competitive Salary
Competitive base salary reflecting Bay Area market rates and your experience level.
Benefits & Wellness
Full health, dental, and vision insurance. Flexible PTO and a team that respects work-life balance.
Growth & Learning
Work at the cutting edge of AI in wealth management. Conference budget, learning stipend, and direct mentorship from senior leadership.