Lead Agentic AI Engineer

Job description

### **About CodeRoad** ### CodeRoad provides end-to-end software development services, helping businesses scale with ideal infrastructure solutions. From staff augmentation to dedicated IT teams and general software engineering, our nearshore technology services empower businesses to thrive in an ever-evolving digital landscape. ### About the Role ### As the **Lead****Agentic AI Engineer**, you will serve as the primary technical authority responsible for architecting, engineering, and operationalizing enterprise-grade autonomous agent systems integrated directly with the **Salesforce** platform. You will lead the implementation of stateful multi-agent workflows, leveraging frontier LLMs (with a strong emphasis on the **Anthropic Claude** ecosystem), Model Context Protocol (**MCP**), and modern orchestration engines to bridge complex business requirements with robust software engineering. This role is critical to transforming enterprise business processes by embedding safe, high-accuracy, and deterministic autonomous AI agents into Salesforce CRM, Data Cloud, and core operational systems. You will anchor the vision, evaluation pipelines, and architectural standards that allow high-throughput agentic workflows to operate securely within strict transactional boundaries and enterprise data security protocols. ### Key Responsibilities - **Architect** stateful multi-agent coordination graphs using **LangGraph** or custom DAG loops, supporting dynamic task decomposition, supervisor orchestration, human-in-the-loop escalation, and automated error recovery. - **Build** standardized **MCP** (Model Context Protocol) servers and connectors to securely expose Salesforce tools, objects, custom actions, and operational context to agent runners. - **Optimize** query routes and context engineering across model tiers (such as **Claude Sonnet/Opus** for multi-turn reasoning vs. **Haiku** for high-throughput utility tasks) to optimize latency, accuracy, and token spend. - **Design** automated evaluation harnesses (**Promptfoo**, **Ragas**, or **DeepEval**) integrated into CI/CD pipelines to continuously benchmark grounding, schema validity, and hallucination resistance against reference datasets. - **Implement** full-stack observability and defense-in-depth security using tools like **LangSmith** or **Langfuse** alongside strict input sanitization, field-level security (**FLS**), and automated **PII** scrubbing. - **Lead** technical delivery standards, establishing API interface contracts, specification-driven development patterns, and architectural blueprints for cross-functional engineering teams and executive stakeholders. ### Requirements - **7+ years** of hands-on enterprise software engineering experience using **Python**, **TypeScript/Node.js**, **Java**, or **Apex**. - **3+ years** of direct production experience building, evaluating, and scaling LLM-powered applications and autonomous multi-agent workflows. - **Tech Stack:** Expert proficiency with **LangGraph** / **LangChain**, **Anthropic/Claude APIs** (tool calling, prompt caching, Claude Code), **MCP**, and observability tools (**LangSmith**, **Langfuse**, or **OpenTelemetry**). - **Evaluation Frameworks:** Hands-on experience with automated LLM eval suites (**Promptfoo**, **Ragas**, or LLM-as-a-judge patterns) as automated test gates. - **Ownership mindset** with deep diagnostic debugging skills for isolating non-deterministic LLM behavior, context degradation, and latency bottlenecks. - **Consultative Communication:** Strong ability to translate complex AI mechanics into actionable architecture roadmaps for technical and non-technical stakeholders. - **Advanced English:** Fluent written and spoken professional English for direct client consultation. ### Nice to Have - Practical integration experience with **Salesforce APIs** (REST, Composite, Bulk), **SOQL/SOSL**, Platform Events, and Connected Apps. - Familiarity with **Salesforce Data Cloud**, vector search capabilities, or **Agentforce** architectural patterns. - Experience deploying containerized **MCP** servers integrated with enterprise CRM security boundaries. - Hands-on exposure to **Spec-Driven Development (SDD)** methodologies for AI-assisted software delivery workflows. ### **Compensation & Benefits** - Candidate must be legally authorized to work in the United States (no sponsorship available). - CodeRoad offers a comprehensive and competitive benefits package, including medical, dental, and vision insurance, retirement plan, and paid time off (PTO). - The salary range for this role is $190,000–$250,000 per year.