Senior Agentic Automation Engineer

Responsibilities

• Lead design and deployment of end-to-end agentic systems that combine reasoning, decision-making, and autonomous execution
• Design multi-agent architectures by applying established agent design patterns and robust cross-agent communication so agents can collaborate or challenge each other to improve outcomes
• Build advanced context and memory capabilities, including dynamic context compression, persistent multi-layer memory (short-term, long-term, episodic, shared), retrieval and forgetting strategies, and supporting infrastructure (vector stores, RAG pipelines, structured logs)
• Develop custom RAG and vector-based retrievers focused on retrieval relevance, latency/throughput optimization, and advanced semantic search (e.g., dense embeddings, hybrid search, re-ranking)
• Orchestrate tools via MCP with a solid grasp of transport layers (HTTP, WebSocket, gRPC) and authentication (OAuth, token-based auth)
• Script in at least one language supported by the platform (e.g., JavaScript, Python) to extend functionality or preprocess data
• Architect secure, auditable pipelines with encryption, access control, PII sanitization, and traceability so that actions can be reviewed and audited
• Work with cloud agent frameworks (e.g., AWS, GCP, Azure) at an intermediate level to design and operate solutions
• Integrate end-to-end observability using LLM-specific observability tooling, OpenTelemetry-based tracing, and infrastructure monitoring to track reliability, performance, and cost of agents and their tools
• Create reusable workflow templates and documentation so other teams can adopt and run agentic automation

Languages