AI Embedded Business Automation Engineer
$130,000–$175,900 year
On-siteNew York City, New York, United States or Houston, Texas, United States
Job Summary
Partner with business stakeholders and subject matter experts to uncover manual handoffs, rework, and exception-heavy processes, then design and deliver AI-enabled workflow redesigns and secure data pipelines. Co-develop practical solutions using Python, LLM APIs, and agent frameworks to integrate with enterprise systems like SharePoint, Teams, Outlook, ERP platforms, and Salesforce. Rapidly prototype, test, and iterate on intelligent assistants and automation logic while embedding security, privacy, and responsible AI controls throughout the lifecycle. Support adoption through SME enablement and feedback loops, then deploy, monitor, and optimize solutions for production reliability and cost management. Define success metrics to measure cycle-time reduction and business capacity gains. Work cross-functionally with engineering, product, and legal teams to move solutions from concept through production launch, aligning with IT governance standards.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, Mathematics, or a related field
- 3+ years of experience in software engineering, automation engineering, cloud engineering, data engineering, integration development, or related technical roles
- experience delivering AI or Generative AI solutions in a business environment
- Experience building workflow automations, APIs, integrations, copilots, assistants, or AI-enabled business applications
- Experience supporting production systems, partnering with cross-functional stakeholders, and translating business needs into secure, scalable technical solutions
- Strong product judgment, communication skills, and delivery orientation
- ability to release useful increments quickly
- ability to recognize when a more durable solution is needed
- ability to write specs, docs, and updates that are clear without additional explanation
- Demonstrated ability to deliver reliable code, services, integrations, or automations used in day-to-day business operations
- Required coding proficiency in Python
- ability to write clean, tested, maintainable code
- ability to contribute effectively to shared production codebases
- Hands-on experience applying LLMs and Generative AI to real business problems
- experience with prompt engineering
- experience with LLM APIs
- experience with retrieval-augmented generation
- experience with AI-enabled workflows
- experience with prototypes, assistants, or agents
- Experience using AI-assisted development tools
- building tool-using workflows
- building custom agents that leverage MCP or similar agent integration patterns
- ability to connect securely to enterprise systems, APIs, data sources, and business applications
- Demonstrated ability to turn business problems into technical specifications, solution designs, implementation plans, and working software
- ability to explain clearly to non-technical partners
- Working knowledge across several core enterprise engineering areas
- knowledge of cloud infrastructure
- knowledge of data engineering
- knowledge of SQL
- knowledge of pipelines
- knowledge of integration patterns
- knowledge of automation tooling
- knowledge of IAM
- knowledge of APIs
- knowledge of enterprise application development
- Familiarity with information security fundamentals
- knowledge of authentication
- knowledge of authorization
- knowledge of encryption
- knowledge of secrets management
- knowledge of safe data practices
- knowledge of least-privilege access
- knowledge of auditability
- knowledge of responsible AI guardrails
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