About the Product<\/p>\n
We are developing a platform of AI analyst coworkers that deliver industry insights. The agents operate in secure, sandboxed environments and can use tools, communicate across channels, and complete complex tasks with human oversight.<\/p>\n
About the Role<\/p>\n
You will join a small engineering team building and operating the platform's agentic AI capabilities. This is a hands-on role covering AI agents, system architecture, production reliability, feature design and secure deployment.<\/p>\n
Tech Stack<\/p>\n
– TypeScript, Node.js, and Bun
– LLM APIs, agent SDKs, and MCP
– SQL and SQLite
– GCP, including Cloud Run, Cloud Build, and Artifact Registry
– Terraform and CI\/CD
– Event-driven messaging and asynchronous processing
– Structured logging, monitoring, and tracing<\/p>\n
Key Responsibilities<\/p>\n
– Design and build production AI agents that can plan, use tools, maintain context, and complete complex tasks.
– Design scalable systems for agent orchestration, messaging, task execution, permissions, and persistent state.
– Integrate LLM providers, external APIs, databases, and communication channels.
– Build secure, sandboxed environments for executing agent workloads.
– Develop evaluation, monitoring, and debugging tools for agent quality and reliability.
– Deploy and operate AI services on GCP.
– Own technical decisions and establish strong engineering, testing, and security practices.<\/p>\n
Required Skills<\/p>\n
– 7+ years of software engineering experience.
– Hands-on experience delivering production AI or agentic systems used by real users.
– Strong system design experience, particularly with distributed and event-driven systems.
– Strong backend development skills in TypeScript, Python, Go, Java, Rust, or a similar language.
– Experience with LLM APIs, tool calling, structured outputs, context management, and agent workflows.
– Experience with SQL databases, asynchronous processing, retries, idempotency, and failure handling.
– Production experience with GCP, Docker, CI\/CD, and infrastructure as code.
– Strong understanding of application security, permissions, secrets, and workload isolation.
– Experience with observability, incident investigation, and production operations.
– Ability to work independently and communicate clearly in a fast-moving environment.<\/p>\n
Nice to Have<\/p>\n
– Experience with agent frameworks such as LangGraph, LangChain, CrewAI, OpenAI Agents SDK, Claude Agent SDK, or similar.
– Experience with Terraform, Kubernetes, vector search, RAG, or multi-agent systems.
– Experience with financial research or analyst workflows.<\/p>\n
Who We Are<\/p>\n
Ad\u00e9lie Cognition builds solutions for a private investment firms and offices powered by latest AI models.<\/p>\n","protected":false},"excerpt":{"rendered":"
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