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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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