Senior Agentic Systems Engineer

About the Role

We’re looking for a Senior Agentic Systems Engineer to lead the design, development, and operation of cutting-edge agentic AI systems across a modern, cloud-based platform. In this role, you will connect internal developer productivity, enterprise intelligence, and user-facing products.

This is a hands-on technical leadership role where you will lead by example through daily coding, architectural design, and mentorship. You will set the technical direction across scalable backends, modern frontend components, and cloud infrastructure, driving the company's AI strategy across three distinct layers:

• Layer 1 (Engineering): Using AI agents to help our team build and test software faster.

• Layer 2 (Company Brain): Unifying internal company data and tools into a single shared intelligence.

• Layer 3 (Customer Features): Shipping predictive, data-driven AI features directly to our external users.

Key Responsibilities

• Build Agent Architecture: Lead the design of agent architectures (planning, memory, multi-step reasoning, tool calling) and build robust backends with clean APIs for React/Web frontends.

• Optimize the SDLC (Layer 1): Design agentic workflows to assist with coding, testing, and CI/CD across our codebases; standardize internal AI developer tools.

• Connect Enterprise Data (Layer 2): Build robust data ingestion, retrieval (RAG), and memory layers over internal systems. Design secure integrations (tool calling, MCP servers) so agents can take action across internal tools.

• Deliver Customer Intelligence (Layer 3): Ship safe, customer-facing predictive features using customer data as context. Ensure strict data isolation, privacy, and multi-tenant security boundaries.

• Set Standards & Cloud Practices: Establish org-wide standards for deploying, monitoring, and cost-optimizing agentic systems on modern Cloud infrastructure.

• Mentor & Guide: Conduct technical reviews, make high-level decisions on model selection, and grow the engineering team's agentic systems expertise.

Qualifications

• 6+ years of software engineering experience, with strong proficiency in at least one modern language (Python, TypeScript/Node.js, C#/.NET, Go, or Java).

• 2+ years of hands-on experience building production applications with LLMs, including advanced prompt engineering and tool/function calling.

• Demonstrated experience shipping agentic or complex LLM systems at scale, including solid knowledge of RAG, vector databases, and context management.

• Experience using AI agents within the software development lifecycle and familiarity with modern AI agent frameworks or protocols (e.g., LangChain, LlamaIndex, Semantic Kernel, AutoGen, or Model Context Protocol / MCP).

• Solid experience with major Cloud Platforms (GCP, AWS, or Azure) using containers, serverless execution, and modern cloud services.

• Expert grasp of API design, distributed systems, asynchronous programming, and multi-tenant security isolation.

• Great communication skills, a collaborative mentoring mindset, and a strong sense of ownership.

Advantages:

• Experience with cloud-native AI services (e.g., Vertex AI, AWS Bedrock, or Azure OpenAI ecosystem).

• Familiarity with cross-language interop and polyglot architecture (e.g., connecting a Python AI engine to a .NET/Go backend).

• Knowledge of LLM observability/evaluation tools (OpenTelemetry, Cloud Monitoring, LangSmith) and AI safety practices.