About Boson AI:

At Boson AI, we are not just building AI solutions; we are pioneering the future of enterprise AI. Driven by a passion for cutting-edge AI research, particularly in the transformative areas of large language models and agentic systems, our mission is to tackle the most complex real-world problems for businesses and unlock significant value. We are a dynamic and collaborative team of researchers and engineers who thrive on pushing the boundaries of what's possible, dedicated to delivering high-quality, reliable products that seamlessly integrate into the fabric of enterprise workflows and set new industry standards.

About the Role:

Engineer and evolve the core Agent OS—a high-performance, resilient platform encompassing the dialog & policy engine, distributed context & memory, execution runtime, security isolation, voice runtime, and complex agentic orchestration frameworks. This system underpins all Boson agents, from low-code configuration flows in Workspace to advanced, production-grade systems leveraging RAG, ReAct, robust tool calling, and multi-step execution.

Responsibilities

• System Ownership: Take ownership of the core dialog & policy engine. Define and implement the state machine for agent state representation, the decision-making logic, and the mechanisms for enforcing complex safety policies and guardrails at the execution layer of a workflow.
• Distributed Context & Memory: Design, implement, and maintain the high-performance context and memory systems. Focus on low-latency, reliable access to conversational and user history, including the tight integration and optimization of RAG and vector retrieval pipelines for production use.
• Agentic Orchestration Frameworks: Define, architect, and deliver robust agentic orchestration patterns, including battle-tested planner–executor schemes, ReAct-style reasoning and acting loops, and resilient, multi-step workflows that programmatically combine tools, LLMs, and stateful memory.
• Internal SDK/Framework Development: Build and evolve the internal, production-grade equivalent of frameworks like LangChain/LlamaIndex. Design composable graphs and execution chains with clear APIs and type safety that product engineering teams and low-code builders can safely reuse, extend, and deploy at scale.
• Voice Runtime Infrastructure: Own and optimize the voice runtime components for streaming audio, low-latency barge-in detection, and reliable turn-taking protocols. This requires deep collaboration with Application and ML Platform teams to meet tight latency, jitter, and quality of service (QoS) constraints.
• Tooling & Integration Architecture: Architect a robust, secure tooling and integration framework (MCP/A2A). This includes building the underlying infrastructure for tool registration, handling complex authentication/authorization, implementing rate limiting/circuit breaking, managing retries, and ensuring typed, validated I/O between agents and external microservices.