Agentic AI Engineer

Responsibilities

• Integrate scalable tool-calling capabilities and standardized connectors using the
• Model Context Protocol (MCP)

Preferred

• Direct experience setting up LLM observability platforms () and automated evaluation/testing frameworks.

Engagement Type

Full-Time / Contractor

About CodeRoad

CodeRoad is a technology execution partner trusted by companies across North America since 2002. We work alongside our clients to engineer, modernize, and scale the technology that powers their businesses, combining deep technical expertise, specialized teams, and shared accountability for outcomes. Our capabilities span product engineering, platform engineering, legacy modernization, and AI engineering.

Our engineers, designers, delivery leaders, and technology specialists collaborate through Velocity Studios: specialized teams developed within CodeRoad to deliver complex technology initiatives. Being assigned to a project means you become part of a collaborative environment where you can strengthen your expertise, take ownership of meaningful work, and grow alongside experienced professionals.

Why Build Your Career at CodeRoad?

High-Velocity Work & Client Exposure

We work close to the technology, teams and roadmaps that move real outcomes. Direct engagement with U.S. client teams and roadmaps.

Career Continuity & Long-Term Opportunity

Your career here can outlast any single project. Continuous multi-project pipeline; long-tenure CodeRoaders.

Engineering Autonomy & Technical Mastery

We invest in the skills that shape what's next. Agentic AI tools and training, Coursera Enterprise, Studio practice labs, L1-L7 Career Framework.

High-Trust Employee Experience

You grow in an environment built on trust, transparency and recognition. High-touch onboarding, transparent leadership communication, community recognition, psychological safety.

Architect Multi-Agent Systems

Design and deploy hierarchical multi-agent workflows using

LangGraph, transitioning legacy single-prompt applications into modular, autonomous systems.

Optimize Token Economics & Latency

Build domain-specific sub-agents featuring dynamic, on-demand context-loading mechanisms to streamline operational security, performance, and token costs.

Implement Observability & Cost Tracking

Manage and configure

LangFuse to maintain complete visibility over LLM reasoning traces, performance metrics, and cost allocation.

Establish Automated Evaluation Harnesses

Lead the creation of regression testing suites and automated eval harnesses using tools like

PromptFlow or

PromptFoo against key benchmark datasets.

Enforce OWASP AI Security Guardrails

Collaborate with security leads to integrate strict access controls and guardrail frameworks aligned with OWASP Top 10 standards for LLM applications.

Software Engineering Depth

• 5+ years of professional backend software development experience, primarily centered around
• Python and scalable architecture.

Agentic AI & Orchestration Expertise

• 2+ years of hands-on experience building production-grade AI agents or complex LLM workflows using
• LangGraph or
• LangChain

Modern AI & Foundation Model Stack

• Deep experience working with foundation models (
• Anthropic Claude

OpenAI

• Google Gemini), open-weights models, advanced prompt engineering, and the
• Microsoft 365 Agents SDK

Observability & Evaluation Proficiency

LangFuse

Cloud & Infrastructure Familiarity

• Practical knowledge of containerized deployments using
• Docker across cloud platforms like
• Azure

Collaboration & Language

• High ownership mindset, empathetic communication style, and advanced English proficiency
• (written and spoken) for direct engagement with U.S. engineering teams.
• What You’ll Love
• USA Contractor / 100% Remote

Competitive Pay (USD)

Holidays Off & Paid Time Off

Health insurance assistance program

Opportunity to work with high-growth US-based companies and cutting-edge tech stacks.

Ready to Build What Actually Ships?

Explore opportunities and submit your application today!