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Senior AI Automation Engineer

AI Engineer Full-time Permanent USA

Job details

Not specified Salary
USA Eligibility
Senior Experience
Full-time Employment

About this role

Role overview

A senior engineering role focused on designing, building, and shipping AI-driven automation across enterprise systems. The position owns an integration platform (Workato) and develops agentic workflows, retrieval-augmented pipelines, and intelligent automations that reduce manual effort and surface business insights. It pairs deep hands-on integration work with practical AI system design in a production environment serving multiple business operations.

Responsibilities

- Design, build, and maintain Workato recipes, connectors, and orchestrations that span Salesforce, NetSuite, Slack, and Snowflake, with reusable patterns and observability built in. - Architect multi-agent systems that include tool selection, planning loops, state management, and human-in-the-loop checkpoints, plus guardrails and recovery paths for non-deterministic workflows. - Operate the full RAG lifecycle, including ingestion, chunking strategy, embeddings, vector storage, and reranking, alongside data quality safeguards. - Implement production observability through prompt and response tracing, cost monitoring, evaluation dashboards, and A/B testing of agent versions and model comparisons. - Write modular Python, Ruby, SQL, or JavaScript to support integration, transformation, and automation tasks. - Apply data governance practices and maintain technical documentation, diagrams, and version control via GitHub, Jira, and Confluence.

Requirements

- At least 5 years in integration, automation, AI, or software engineering, including 1 or more years of hands-on Workato experience. - Demonstrated enterprise iPaaS expertise (Workato, MuleSoft, or comparable) integrating Salesforce, NetSuite, Slack, and Snowflake. - Strong programming background in Python, Ruby, or similar languages, leveraging APIs to build scalable enterprise systems. - Hands-on experience with vector databases such as Pinecone, Snowflake Cortex Search, or pgvector supporting RAG workloads. - Practical background implementing agentic architecture and AI workflows inside enterprise environments. - Familiarity with GitHub for version control, Jira for work tracking, and Confluence or Lucid for documentation.

Nice to have

- Experience with cloud platforms such as GCP or AWS. - Self-directed problem-solving ability and motivation to learn new tools quickly. - A track record of introducing innovation in automation.

Skills detected in the listing

JavaScriptPythonRubySQLSnowflakeStakeholder ManagementAWSGCP
Detected Sep 11, 2026
Last verified Sep 11, 2026

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