Senior AI Engineer (Architect) – Enterprise Business Process Automation

Title: Senior AI Engineer (Architect) – Enterprise Business Process Automation
Location : Remote (EST business hours)
Target Start Date : ASAP
Type: Contract
Pay Rate : $90.00-$110.00/hr (negotiable DOE)

Overview
We are seeking aSenior AI Engineer (Architect) to define and lead the enterprise strategy for AI-driven business process automation. This role is responsible for shaping thearchitecture, governance, and scalable adoption of AI technologies across core business functions, enabling intelligent, data-driven, and increasingly autonomous operations.
As a senior technical leader, you will operate at the intersection ofAI, data, and enterprise systems, guiding the organization in leveragingagentic AI, advanced analytics, and modern data platforms to transform end-to-end processes across manufacturing, supply chain, and corporate domains.

• Define and own theenterprise AI architecture, includingLLM-based systems, agentic AI frameworks, and decision intelligence platforms.
• Establishreference architectures and design patterns for scalable AI solutions (e.g., RAG, multi-agent systems, knowledge-driven AI).
• Architect integration betweenAI systems, enterprise applications, and data platforms (data lakes, warehouses, lakehouses).
• Drive alignment of AI initiatives withenterprise data strategy, governance, and analytics frameworks.

• Lead the identification and prioritization ofhigh-value AI automation opportunities across key business domains:
  • Sales & commercial operations
  • Supply chain, logistics, and inventory
  • Finance (P2P, O2C, R2R)
  • HR and payroll
• Define howagentic AI and intelligent workflows can re-architect business processes—not just optimize them.
• Partner with executive and functional leaders to align AI initiatives withbusiness outcomes, ROI, and transformation goals.

• Evaluate and define the enterprise approach toAI platforms and tooling, including:
  • Multi-cloud AI services (Azure, AWS, Google Cloud)
  • Data platforms (Snowflake, Databricks, BigQuery)
  • LLM frameworks and orchestration tools (LangChain, Semantic Kernel, etc.)
• Establish standards formodel selection, orchestration, integration, and scalability.
• Guide build vs. buy decisions and ensureinteroperability across the AI ecosystem.

• Ensure AI solutions are built on a strong foundation ofdata architecture and governance, including:
  • Data lakes, warehouses, and lakehouse models
  • Data quality, lineage, and accessibility
  • Real-time and batch data processing
• Champion the use of AI to enhanceenterprise analytics, forecasting, and decision support.
• Drive convergence ofAI, BI, and advanced analytics into unified decision intelligence capabilities.

• Define and implementAI governance frameworks, including responsible AI, security, compliance, and model risk management.
• Establish enterprise standards forMLOps/LLMOps, monitoring, observability, and lifecycle management.
• Ensure AI systems arescalable, secure, auditable, and aligned with regulatory requirements.

• Serve as athought leader and advisor to senior leadership on AI strategy, capabilities, and roadmap.
• Mentor engineering teams and influence adoption ofAI-first and data-driven practices across the organization.
• Foster collaboration acrossIT, Engineering, Data, and Business functions to ensure successful execution of AI initiatives.

• 10–15 years of experience insoftware engineering, data engineering, or enterprise architecture, with significant focus onAI/ML solutions.
• Proven track record defining and deliveringenterprise-scale AI and automation strategies.
• Deep expertise in:
  • AI/ML architectures, including LLMs, RAG, and agentic systems
  • Enterprise data platforms (data lakes, warehouses, lakehouse architectures)
  • System integration and enterprise architecture patterns
• Experience acrossmulti-cloud AI ecosystems and platforms, includingMicrosoft (Copilot, Azure AI), AWS, Google Cloud, and modern data platforms (Snowflake, Databricks, etc.)Strong understanding ofbusiness process architecture and enterprise systems (ERP, CRM, MES, HRIS).
• Experience establishinggovernance, MLOps/LLMOps frameworks, and scalable AI platforms.
• Ability to translatebusiness strategy into technical architecture and execution roadmaps.

• Experience inmanufacturing, supply chain, or industrial environments.
• Familiarity withIoT/edge data, real-time analytics, and operational systems.
• Background indigital transformation, process re-engineering, or enterprise architecture (TOGAF, etc.).

• Define and scale the organization’senterprise AI and automation strategy
• Transform core business processes throughintelligent, autonomous systems
• Enabledata-driven decision-making and operational excellence at scale
• Establish a foundation forlong-term AI innovation and competitive advantage

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