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 a Senior AI Engineer (Architect) to define and lead the enterprise strategy for AI-driven business process automation. This role is responsible for shaping the architecture, 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 of AI, data, and enterprise systems, guiding the organization in leveraging agentic AI, advanced analytics, and modern data platforms to transform end-to-end processes across manufacturing, supply chain, and corporate domains.
Key Responsibilities
AI & Data Architecture Leadership
- Define and own the enterprise AI architecture, including LLM-based systems, agentic AI frameworks, and decision intelligence platforms.
- Establish reference architectures and design patterns for scalable AI solutions (e.g., RAG, multi-agent systems, knowledge-driven AI).
- Architect integration between AI systems, enterprise applications, and data platforms (data lakes, warehouses, lakehouses).
- Drive alignment of AI initiatives with enterprise data strategy, governance, and analytics frameworks.
Enterprise Automation Strategy
- Lead the identification and prioritization of high-value AI automation opportunities across key business domains:
- Sales & commercial operations
- Supply chain, logistics, and inventory
- Finance (P2P, O2C, R2R)
- HR and payroll
- Define how agentic AI and intelligent workflows can re-architect business processes—not just optimize them.
- Partner with executive and functional leaders to align AI initiatives with business outcomes, ROI, and transformation goals.
Platform & Technology Strategy
- Evaluate and define the enterprise approach to AI 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 for model selection, orchestration, integration, and scalability.
- Guide build vs. buy decisions and ensure interoperability across the AI ecosystem.
Data & Analytics Enablement
- Ensure AI solutions are built on a strong foundation of data 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 enhance enterprise analytics, forecasting, and decision support.
- Drive convergence of AI, BI, and advanced analytics into unified decision intelligence capabilities.
Governance, Risk & Operationalization
- Define and implement AI governance frameworks, including responsible AI, security, compliance, and model risk management.
- Establish enterprise standards for MLOps/LLMOps, monitoring, observability, and lifecycle management.
- Ensure AI systems are scalable, secure, auditable, and aligned with regulatory requirements.
Leadership & Influence
- Serve as a thought leader and advisor to senior leadership on AI strategy, capabilities, and roadmap.
- Mentor engineering teams and influence adoption of AI-first and data-driven practices across the organization.
- Foster collaboration across IT, Engineering, Data, and Business functions to ensure successful execution of AI initiatives.
Required Qualifications
- 10–15+ years of experience in software engineering, data engineering, or enterprise architecture, with significant focus on AI/ML solutions.
- Proven track record defining and delivering enterprise-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 across multi-cloud AI ecosystems and platforms, including Microsoft (Copilot, Azure AI), AWS, Google Cloud, and modern data platforms (Snowflake, Databricks, etc.)Strong understanding of business process architecture and enterprise systems (ERP, CRM, MES, HRIS).
- Experience establishing governance, MLOps/LLMOps frameworks, and scalable AI platforms.
- Ability to translate business strategy into technical architecture and execution roadmaps.
Nice to Have
- Experience in manufacturing, supply chain, or industrial environments.
- Familiarity with IoT/edge data, real-time analytics, and operational systems.
- Background in digital transformation, process re-engineering, or enterprise architecture (TOGAF, etc.).
Impact
- Define and scale the organization’s enterprise AI and automation strategy
- Transform core business processes through intelligent, autonomous systems
- Enable data-driven decision-making and operational excellence at scale
- Establish a foundation for long-term AI innovation and competitive advantage
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