How We Work: Agentic-First Engineering
At JTL, AI-assisted development is not optional - it’s how we build. Engineers on our team actively uses tools like GitHub Copilot, Claude Code, Cursor, or similar AI coding assistants as part of their daily workflow. We expect you to bring experience with these (or similar) tools.
Your Responsibilities
- You own end-to-end system architecture for agentic AI applications, from high-level design through production deployment, scaling, and observability.
- You design and build multi-agent orchestration systems using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or custom orchestration layers.
- You architect scalable, fault-tolerant backend services using Python (FastAPI, async patterns) with clean API contracts (REST, GraphQL, gRPC) consumed by internal teams and external clients.
- You implement cloud deployment strategies on Azure (AKS, Azure AI Services, Functions),or other cloud, including infrastructure-as-code, CI/CD pipelines, and cost governance.
- You design integration patterns for connecting agents to external tools, APIs, databases, and enterprise systems in a secure and extensible way.
- You establish architectural standards, design patterns, and engineering best practices for the AI engineering team (code quality, testing, security, documentation).
- You evaluate emerging agentic AI technologies, LLM providers, and tooling; present technical recommendations and trade-off analyses to leadership.
- You mentor and grow junior and mid-level engineers through architecture reviews, code reviews, and knowledge-sharing sessions.
