About The Role
The Sr. AI Engineer is a highly technical role dedicated to building and deploying production-level AI solutions at Fundraise Up. Partnering closely with the Sr. AI Business Manager, you will take strategic blueprints and turn them into scalable, robust technical realities. This role demands deep expertise in modern AI frameworks, from RAG-based systems to complex agentic architectures, ensuring that our technical deployments are secure, efficient, and deeply integrated into our operational workflows.
What You'll Do
- Agent Architecture Design: Define precise technical requirements for scalable agent architecture, including necessary reasoning frameworks, risk management systems, and knowledge retrieval interfaces required for complex decision-making.
- End-to-End Build Capability: Serve as the hands-on technical lead capable of building, testing, and deploying both interim (e.g., RAG-based systems) and highly complex agentic AI solutions.
- Technical Implementation: Work alongside strategy leads to ensure that the technical prerequisites for achieving fully autonomous agentic operations are met on the twelve-month roadmap.
- Operational Scaling & Integration: Oversee the technical integration and scaling of deployed AI agents within specific operational workflows (e.g., automating specific GTM tasks).
- Validation & Testing: Ensure seamless deployment with rigorous validation testing, monitoring agent performance, and iterating on technical builds to improve decision accuracy and reduce latency.
- At Fundraise Up, AI is a default tool, not an experimental one. We expect every team member to actively use AI in their day-to-day work, identify where AI can change the shape of problems in their function, and grow their fluency as the tools evolve. You should already be using AI meaningfully in your work and understand where it adds value and how it can improve the way you operate.
About You
- 5+ years in software engineering, AI engineering, or technical architecture within high-growth technology environments or AI startups.
- Proven hands-on experience in the technical build and deployment of LLM-powered applications, RAG systems, and agentic workflows.
- Deep understanding of the modern AI tech stack, prompt engineering, API integrations, and scalable deployment infrastructure.
- Proven ability to execute complex technical work streams with limited oversight and high accountability.
- Strong technical communicator; able to explain complex architectural decisions and technical trade-offs to non-technical strategic partners.
- A practical, shipping-oriented approach — you are motivated by building reliable, production-ready systems that solve real business problems.