Title of Role: Software Engineer, AI/ML (GenAI)
Location: San Francisco Bay Area, CA
Company Stage of Funding: Venture-Backed, High-Growth Startup (YC-backed)
Office Type: Hybrid (1 Day Per Week In-Office)
Salary: $175,000 – $220,000 Base + Equity + Benefits
Our client is a rapidly growing, venture-backed SaaS company building technology that empowers nonprofit organizations to discover, track, and manage grant funding more effectively. Their platform supports thousands of organizations — from local community groups to globally recognized institutions — helping them secure funding that supports education, conservation, healthcare, and social impact initiatives.
The company is profitable, growing quickly, and serving over 4,000 organizations across the nonprofit sector. With a strong product-market fit and a passionate customer base, the team is focused on building innovative AI-driven features that improve fundraising workflows and unlock new insights for their users.
This is an opportunity to join a mission-driven company where the work you ship directly supports organizations making meaningful contributions to communities and the world.
As a Software Engineer, AI/ML (GenAI), you will play a key role in designing and deploying production-grade AI features that power the company’s platform. This role focuses on building scalable systems that leverage modern large language models and machine learning techniques to deliver real value to users.
You will:
Design, build, and deploy LLM-powered features and AI systems from concept through production.
Develop and maintain Retrieval-Augmented Generation (RAG) pipelines, including data ingestion, chunking strategies, embedding pipelines, and retrieval optimization.
Build and operate scalable vector database and embedding infrastructure to support high-performance AI features.
Implement evaluation frameworks and observability systems to monitor model performance, accuracy, and cost efficiency.
Collaborate with product, design, and engineering teams to translate customer needs into intelligent AI-powered experiences.
Improve reliability and scalability of AI systems operating in production environments.
Contribute to architecture decisions around AI infrastructure and data pipelines.
This is a high-impact role where engineers own projects end-to-end and ship features that directly improve how thousands of organizations access funding opportunities.
The ideal candidate is a strong software engineer who has transitioned into building AI-powered applications and has experience taking LLM systems from prototype to production.
Candidates will typically have:
5–8 years of software engineering experience building production systems.
Strong proficiency in Python and modern backend development practices.
Experience building production-grade LLM or NLP systems, not just prototypes.
Hands-on experience with RAG pipelines, embeddings, and vector databases.
Experience building scalable APIs, services, and distributed systems.
A track record of shipping features in startup or high-growth environments.
Strong problem-solving ability and comfort working across the full development lifecycle.
While not required, the following experience would be beneficial:
Experience building agentic LLM workflows using frameworks such as LangChain, LlamaIndex, or similar tooling.
Experience with vector databases and embedding management at scale.
Experience designing evaluation frameworks for LLM outputs.
Experience working at AI-first companies or startups building AI-driven products.
Experience with ML infrastructure, model observability, or prompt optimization.
Base Salary: $175,000 – $220,000
Equity: Meaningful equity participation
Benefits: Comprehensive health, dental, and vision coverage
Work Environment: Hybrid work model with a collaborative engineering culture
Relocation Support: Available for candidates moving to the Bay Area
Impact: Build technology used by thousands of organizations doing meaningful work around the world
This is an excellent opportunity for engineers who want to build real-world AI systems, ship quickly, and work on meaningful problems in a fast-growing environment.
If you are excited about building production AI systems that power real customer workflows, we encourage you to apply.