AI Agent Engineer

About us Symbolica was founded on a simple idea: intelligence is about structure and reasoning, not just pattern matching. For decades, AI has been split between symbolic systems that are reliable but brittle and neural systems that are flexible but unpredictable. We’re building a bridge between the two. We’re an AI research lab combining deep mathematics and machine learning to create systems that truly reason. Using category and type theory as a unifying framework, we develop interpretable, reliable and scalable foundations for intelligence and turn them into real products, working in a tight feedback loop where research directly shapes application. Agentica is the latest expression of this vision: an agent framework for tool use and multi-agent orchestration through arbitrary code execution. It recently achieved 85.28% on ARC-AGI-2, setting a new public SOTA. Founded in 2022, we’ve raised over $30M from investors including Khosla Ventures, General Catalyst, Abstract Ventures and Buckley Ventures, backing us to rethink the mathematical foundations of machine learning. If you’ve ever been kept awake wondering what comes after deep learning, you’ll fit right in. About the Role We’re looking for an AI Agent Engineer – a software engineer with deep experience in ML, LLMs, and/or agentic systems – to help push the limits of our internal agent framework and shape its design. You’ll work side-by-side with researchers, ML engineers, and leadership to turn ambitious ideas into real-world systems. Expect to move fast, handle ambiguity, and fill the critical execution gap between research and production. 📍 This is an onsite role based in our SF office (345 California St). Your Focus 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. About You 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. Nice-to-haves Experience with autonomous, dynamic multi-agent systems (beyond DAGs). Context engineering expertise. Embedding models RAG. Improving model performance via fine-tuning. What We Offer Competitive salary + early-stage equity package. High-trust, execution-first culture with minimal bureaucracy. Direct ownership of meaningful projects with tangible impact. A rare chance to work at the interface of deep research and real-world productization. Candidates for this position must be legally authorized to work in the United States. This position is not eligible for visa sponsorship or support. Read more about Symbolica: https://fortune.com/2024/04/09/vinod-khosla-former-tesla-autopilot-engineer-ai-models/ https://venturebeat.com/ai/move-over-deep-learning-symbolicas-structured-approach-could-transform-ai/ Symbolica is an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, gender, age, religion, disability, or sexual orientation. ... (truncated, view full listing at source)