AI Embedded Business Automation Engineer

Quick Facts

• Role: AI Embedded Business Automation Engineer

Description

This role designs, prototypes, and delivers AI- and automation-driven solutions that improve day-to-day business operations across functional teams. You will translate business needs into actionable technical requirements, scalable AI/data architectures, and production implementation plans, while communicating recommendations to both technical and nontechnical leadership. The engineer will build end-to-end agentic/automation solutions, integrations, and trustworthy AI components—ensuring security, governance, reliability, and measurable impact.

Responsibilities

• Engage business leaders and SMEs to identify strategic priorities, requirements, and opportunities for AI and automation

• Uncover manual handoffs, delays, and exception-heavy processes; co-design improved workflows

• Create architectural designs, implementation plans, and delivery milestones; write clear specs and documentation

• Rapidly prototype, test, and iterate AI-driven automations, assistants, agents, and workflow solutions

• Build and maintain integrations with enterprise systems (e.g., SharePoint, Teams, Outlook, ERP, Salesforce, internal apps)

• Implement trustworthy AI components (prompt orchestration, RAG pipelines, document ingestion, vector search, secure access patterns)

• Embed security, privacy, compliance, and responsible AI controls across the solution lifecycle

• Deploy, monitor, troubleshoot, optimize, and continuously improve production AI/automation solutions

• Document architecture and create reusable patterns aligned with IT governance

• Define success metrics and measure impact (cycle-time reduction, quality, adoption, reliability, unlocked capacity)

• Drive adoption with SME enablement, training, feedback loops, and usage-based refinement

Requirements

• Bachelor's degree in a relevant field (or equivalent practical experience)

• 5-7+ years in relevant technical roles with experience delivering AI/Generative AI in business contexts

• Experience building workflow automations, APIs, integrations, copilots, assistants, or AI-enabled business applications using Microsoft/Azure/OpenAI (or comparable enterprise platforms)

• Strong Python coding skills for clean, tested, maintainable production code

• Hands-on LLM/Generative AI experience for business problems, including prompt engineering and RAG

• Experience with tool-using agent patterns (e.g., MCP) and secure integration to enterprise systems, APIs, and data sources

• Working knowledge across cloud, data engineering (SQL/pipelines), integration patterns, automation tooling, IAM, and enterprise application development

• Familiarity with information security fundamentals (least privilege, encryption, secrets management, auditability) and responsible AI guardrails

• Ability to independently lead AI and data architecture decisions and own delivery with limited support

Benefits

• Professional development and competitive rewards

• Comprehensive benefits

• Culture grounded in trust and high standards

• Opportunities to take on meaningful responsibility and evolve your career