AI Engineer

Quick Facts

• Role: AI Engineer

• Focus: Production-grade LLM and agentic systems for enterprise workflow automation

Description

You will design and develop AI agents that can handle multi-step business workflows and coordinate real-world tasks. The role combines LLM-based reasoning with conventional Python services, including tool discovery (with MCP), integrations via REST APIs, and graph-based workflow orchestration with state and human approval steps. You will optimize reliability, response time, and cost for production AI applications.

Responsibilities

• Design and develop AI agents for multi-step tasks and business workflows

• Build agent architectures combining LLM reasoning with Python services

• Develop APIs and integrations with enterprise applications

• Create agent tools, including MCP-based tools

• Orchestrate workflows using graph-based approaches, including state management and human approvals

• Enable communication and cooperation between multiple AI agents

• Improve reliability, latency, and cost efficiency

• Collaborate with engineers, architects, and business stakeholders

• Contribute to production architectures, testing strategies, and operational practices

Requirements

• Strong software engineering experience with hands-on delivery of LLM or agent-based applications

• Advanced Python with asyncio, FastAPI (or comparable), Pydantic, and pytest/pytest-asyncio

• Solid LLM application development knowledge: tool/function calling, structured outputs, agent orchestration, multi-agent architectures, workflow automation, and latency/cost optimization

• Commercial experience with an agent/LLM framework such as LangChain, LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK, or comparable

• Practical knowledge of MCP and experience developing/integrating agent tools

• Experience with workflow orchestration and stateful AI processes

• Experience integrating through REST APIs

• Understanding of authentication/authorization (OAuth2, SSO, Microsoft Entra ID/Azure AD)

• Experience with Redis or a comparable distributed cache/data solution

• Familiarity with Docker and containerized applications

Benefits

Hands-on role building robust, maintainable enterprise AI solutions beyond chatbots—agents that plan, execute, and coordinate real-world tasks.