Lead Agentic AI Engineer

Engagement Type: Full-Time

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.

Key Responsibilities

Architect Multi-Agent Orchestration Systems: Design and deploy stateful multi-agent coordination graphs using LangGraph or custom DAG loops, enabling dynamic task decomposition, supervisor orchestration, human-in-the-loop escalation, and self-healing error recovery.

Engineer MCP Interfaces & Connectors: Build standardized Model Context Protocol (MCP) servers and connectors to securely expose Salesforce tools, custom objects, actions, and enterprise context to autonomous agent runners.

Optimize Reasoning, Latency & Token Spend: Architect multi-tiered LLM routing strategies across model tiers (utilizing Claude 3.5 Sonnet/Opus for complex multi-turn reasoning and Haiku for high-throughput utility tasks) to balance latency, accuracy, and API costs.

Establish Automated Evaluation Pipelines: Implement automated eval harnesses ( Promptfoo , Ragas , DeepEval ) within CI/CD pipelines to continuously measure context grounding, schema validity, and hallucination resistance against golden benchmark datasets.

Enforce Defense-in-Depth Security & Observability: Implement end-to-end telemetry and security using LangSmith or Langfuse , combined with input sanitization, field-level security (FLS) compliance, and automated PII scrubbing.

Lead Technical Strategy & Architecture Standards: Establish specification-driven development patterns, clear API contracts, and architectural blueprints, communicating technical trade-offs directly to engineering teams and C-suite stakeholders.

What You Bring

7+ Years of Enterprise Software Engineering: Proven experience building robust software systems in Python , TypeScript / Node.js , Java , or Apex .

3+ Years of Production AI / LLM Experience: Demonstrated track record designing, evaluating, and scaling production autonomous agent systems and RAG architectures in enterprise environments.

Agentic AI & Tooling Mastery: Deep expertise with LangGraph , LangChain , Anthropic / Claude APIs (tool calling, prompt caching, Claude Code), MCP , and observability suites ( LangSmith , Langfuse , OpenTelemetry ).

Rigorous Evaluation Mechanics: Direct experience setting up automated test gates using Promptfoo , Ragas , or LLM-as-a-judge frameworks to monitor non-deterministic behavior and context degradation.

Proactive Ownership & Diagnostic Skills: High autonomy to isolate complex latency bottlenecks, debug agent routing loops, and turn ambiguous enterprise needs into secure, deterministic technical realities.

Advanced English Fluency: Exceptional written and spoken English communication skills for direct technical leadership and consultation with U.S.-based client executives.

Legal Authorization: Legal authorization to work in the United States.

Bonus Ecosystem Exposure: Hands-on experience with Salesforce APIs (REST, SOQL/SOSL, Platform Events), Salesforce Data Cloud , vector search, Agentforce , containerized MCP deployments, or Spec-Driven Development (SDD) is a strong plus.

What You’ll Love

Competitive Pay ($190,000–$250,000 USD / year)

Comprehensive Benefits Package (Medical, Dental, Vision & Retirement Plan)

Holidays Off & Paid Time Off (PTO)

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!