AI Engineer
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Job Description
Agentic AI Engineer building LangGraph-based multi-agent systems for CodeRoad, a technology execution partner delivering product, platform, modernization, and AI engineering. Optimizing LLM workflows, observability, evaluation, and security.
Responsibilities:
- Design and deploy hierarchical multi-agent workflows using LangGraph
- Transition legacy single-prompt applications into modular, autonomous systems
- Build domain-specific sub-agents with dynamic, on-demand context-loading mechanisms
- Optimize operational security, performance, latency, and token costs
- Integrate scalable tool-calling capabilities and standardized connectors using the Model Context Protocol (MCP)
- Manage and configure LangFuse for LLM reasoning traces, performance metrics, and cost allocation
- Create regression testing suites and automated evaluation harnesses using PromptFlow or PromptFoo
- Collaborate with security leads to integrate access controls and OWASP Top 10-aligned guardrail frameworks for LLM applications
Requirements:
- 5+ years of professional backend software development experience, primarily centered around Python and scalable architecture
- 2+ years of hands-on experience building production-grade AI agents or complex LLM workflows using LangGraph or LangChain
- Deep experience working with foundation models including Anthropic Claude, OpenAI, and Google Gemini
- Experience with open-weights models and advanced prompt engineering
- Experience with Microsoft 365 Agents SDK
- Direct experience setting up LLM observability platforms such as LangFuse
- Experience with automated evaluation/testing frameworks
- Practical knowledge of containerized deployments using Docker across cloud platforms like Azure
- High ownership mindset and empathetic communication style
- Advanced English proficiency, written and spoken
- Ability to engage directly with U.S. engineering teams
Benefits:
- Continuous multi-project pipeline
- Agentic AI tools and training
- Coursera Enterprise
- Studio practice labs
- L1-L7 Career Framework
- High-touch onboarding
- Transparent leadership communication
- Community recognition
- Psychological safety
- Holidays off
- Paid time off
- Health insurance assistance program
- Opportunity to work with high-growth US-based companies and cutting-edge tech stacks
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