AI Operations Engineer

Role Overview

AI and Automation

• Develop AI agents that automate manual and repetitive Commerce Operations tasks.
• Implement workflows using LLM reasoning, tool and function calling, retrieval, and agent orchestration.
• Support agent-to-agent integrations using A2A and MCP standards.
• Implement guardrails, human approval steps, LLM routing, and failover mechanisms.

Integrations and RAG

• Develop secure REST, GraphQL, webhook, and event-driven integrations with commerce platforms and enterprise data sources.
• Apply authentication, rate limiting, validation, and error handling to integrations.
• Build retrieval-augmented generation pipelines using documents, structured data, and enterprise knowledge repositories.
• Apply prompt and context engineering to improve accuracy, safety, and consistency.

Operations and Collaboration

• Contribute to testing, evaluation, tracing, audit logging, monitoring, and quality regression detection.
• Support CI/CD, version control, deployment, rollback processes, monitoring, and cost tracking.
• Monitor performance and report efficiency, cycle-time, incident, and accuracy outcomes.
• Collaborate with operations, application development, infrastructure, and business teams.

Minimum Qualifications

• 3+ years of experience in software engineering, AI engineering, data engineering, or a related field.
• Experience developing LLM-powered, machine-learning, or automation applications.
• Proficiency in Python and one or more LLM or agent frameworks.
• Working knowledge of RAG, prompt engineering, tool or function calling, and workflow orchestration.
• Experience with API and system integrations and enterprise data sources.
• Familiarity with Git, testing, debugging, code reviews, and CI/CD.
• Ability to solve technical problems and collaborate with business and engineering teams.

Preferred Qualifications

• Familiarity with A2A, MCP, OpenAPI-based tool integration, multi-agent systems, and AI agent guardrails.
• Experience with evaluation and observability tools such as LangSmith, Langfuse, or equivalent platforms.
• Knowledge of vector databases, semantic search, hybrid search, reranking, or knowledge-graph grounding.
• Familiarity with AI governance, safety practices, access controls, audit logging, and PII handling.
• Experience with AWS, GCP, or Azure and exposure to MLOps or LLMOps practices.
• Understanding of commerce platforms, commerce operations, supply chain operations, or related processes.
• Bachelor's or master's degree in a relevant technical field or equivalent practical experience.