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Principal AI Architect
2 weeks ago
About Fincore
- We're building the next generation of finance technology using AI.
- Our core values - ownership, customer obsession, truth-seeking, and velocity - guide everything we do.
- We collaborate with seasoned technology, finance and AI leaders.
- We maintain a small, talent-dense team of domain experts and technologists.
What We're Looking For
We need an extremely talented Lead to Principal-Level AI engineer to help us pioneer the future of finance and accounting. The ideal candidate has experience building high-quality, complex yet maintainable LLM apps and agents. They should be able to do so in a fraction of the time that most competent people think is possible. This is due to their ability to wield the latest in code generation and intuition for prompt engineering.
As a Lead AI Engineer, you will:
- Architect and build the core AI platform that powers finance and accounting solutions.
- Design, develop, and productionize large-scale LLMs, RAG pipelines, and autonomous agents.
- Define and enforce best practices for prompt engineering, model fine-tuning, and evaluation.
- Mentor and grow a team of AI engineers, guiding technical design reviews and code quality.
- Partner closely with Product, Data, and Customer teams to translate finance use cases into robust, scalable solutions.
Must-Have Skills
- 8+ years of experience building backend services in Python, Node.js, or similar.
- Deep experience and intuition with LLMs.
- Cutting-edge knowledge of code generation and prompting techniques.
- Experience building agents and tooling for agents.
- Expertise in API design (REST, GraphQL) and relational databases.
- Strong problem-solving, communication, and collaboration skills.
Good to Have
- Top-tier institutes preferred.
- Experience building fintech software.
- Experience working in a large enterprise / big tech.
Tech Stack: NextJS | Python | LangGraph | AWS | Neo4j | PostgreSQL | MongoDB
A successful candidate will have experience with AI platforms, including designing, developing, and productionizing large-scale language models. They must also have expertise in prompt engineering and model fine-tuning, as well as strong collaboration and leadership skills.