Full-Time
AI Agent Engineer
Symbolica AI
11-50 employees
Category-theory based structured AI reasoning
No salary listed
No H1B Sponsorship
San Francisco, CA, USA
In Person
On-site role; SF office at 345 California St.
 AI & Machine Learning (1) |
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- Deep understanding of LLM architecture and inference-time optimisation
- Strong knowledge of the agentic ecosystem (frameworks, tools, MCP servers, MAS architectures)
- Track record of rapid prototyping in the LLM/agent space
- Experience orchestrating and evaluating complex multi-agent systems
- Solid software engineering skills in Python and/or TypeScript
- Must be legally authorized to work in the United States; this position is not eligible for visa sponsorship or support
- Design new agentic systems in our framework that were previously infeasible elsewhere — and test their limits
- Implement and evaluate open-source agentic systems (and customer-specific ones) within our framework
- Identify and solve bottlenecks in today’s agent ecosystem (e.g. context engineering, MCP constraints, inter-agent communication, memory)
- Stay ahead of the curve by tracking new research and incorporating cutting-edge AI features as they’re released
- Experience with autonomous, dynamic multi-agent systems (beyond DAGs)
- Context engineering expertise
- Embedding models & RAG
- Improving model performance via fine-tuning
Symbolica AI uses category theory to build AI models that reason with structured, inductive approaches rather than just predicting tokens. By embedding mathematical structure into inputs, outputs, and reasoning, the models can perform code synthesis and theorem proving more accurately and efficiently, while needing smaller datasets and less compute. The focus on compliance and interpretability aims to reduce hallucinations and produce explainable, verifiable results, which is important for sensitive fields like legal, medical, and financial services. Compared to traditional large language models, Symbolica emphasizes structured reasoning and transparency, enabling faster training and deployment and giving a competitive edge through reliability and formal reasoning capabilities.
Company Size
11-50
Company Stage
Series A
Total Funding
$33M
Headquarters
San Francisco, California
Founded
2022
Simplify's Take
What believers are saying
- Merck pilot doubles drug screening speed, cuts costs 20%.
- Coding assistant pilots with Merck, JPMorgan; Q1 2026 release.
- $20M bridge at $120M valuation from Khosla, General Catalyst.
What critics are saying
- OpenAI o1 surpasses in reasoning benchmarks, diverts pilots within 6-12 months.
- Merck terminates pilot after 10% gains vs. AlphaCode 2 in 3-6 months.
- DeepMind open-sources toolkit, commoditizes IP within 12-18 months.
What makes Symbolica AI unique
- Symbolica leverages category theory for structured inductive reasoning beyond token prediction.
- Neurosymbolic models outperform OpenAI’s o1 by 15% in Alzheimer’s molecular simulations.
- Eradicates hallucinations via algebraic structures for verifiable AI outputs.
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Benefits
Company Equity
Growth & Insights and Company News
6 month growth
↓ -9%1 year growth
↓ -4%2 year growth
↑ 11%SAN FRANCISCO (Diya TV) - Vinod Khosla, renowned for his early investment in OpenAI, is doubling down on AI innovation with Symbolica, a startup launching today with a $33 million Series A funding round led by Khosla Ventures.
Beyond Transformers: Symbolica launches with $33M to change the AI industry with symbolic models - SiliconANGLE
In addition to its public launch, Symbolica revealed today it has raised $33 million in total funding (Series A + seed), led by Khosla Ventures, with participation from Day One Ventures, General Catalyst, Abstract Ventures and Buckley Ventures.
Symbolica raises $31 million to develop AI systems to compete with OpenAI.