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Drive new business and pipeline growth across Middle East industrial accounts, particularly Oil & Gas, Utilities, and Power Generation. Build executive relationships, lead consultative sales cycles, develop operational improvement business cases, leverage channel partnerships, and present Avathon’s Industrial AI platform and use cases. Maintain Salesforce and HubSpot data, collaborate cross-functionally, and travel approximately 30–50% to Saudi Arabia.

Lead development of a Computational Knowledge Graph platform, including ontology and schema design, enterprise data ingestion, Gremlin and SQL query optimization, C++ graph-processing components, analytics integrations, APIs, and cloud services. The role partners with product and data science teams to deliver graph-based solutions, contributes to architecture and technical roadmaps, and mentors engineers. Candidates need strong Python, C++, graph database, query optimization, API, and cloud experience.

Lead outbound engagement and pipeline development across enterprise accounts for Avathon’s industrial AI platform. Build executive relationships, coordinate strategic meetings, leverage channel partnerships, support CEO-office initiatives, articulate AI use cases, maintain Salesforce and HubSpot activity, and collaborate with marketing, sales, product, and leadership teams to drive account growth.

Leads cloud operations for a multi-cloud industrial AI platform across SaaS, customer-managed Kubernetes, edge, on-premise, and air-gapped environments. Owns reliability, incident response, infrastructure automation, CI/CD, security baselines, compliance support, cloud costs, capacity planning, and customer deployments. Leads and mentors cloud and DevOps engineers while partnering with engineering, data, ML, and customer-facing teams. This is a hands-on role involving infrastructure design, automation, on-call support, and operational standards.

Own end-to-end architecture and production delivery for enterprise industrial AI deployments. Design knowledge graphs, agentic workflows, computer vision systems, industrial data integrations, cloud and edge infrastructure, security controls, evaluation frameworks, and AIOps observability. Lead architecture governance across customer engagements, mentor forward-deployed engineers, manage technical risk, and advise senior IT, OT, and engineering stakeholders. The role requires extensive travel to client sites and collaboration across engineering, data science, and customer operations teams.

Designs, develops, deploys, and monitors production-grade machine learning and Generative AI solutions, with emphasis on LLMs, transformer architectures, RAG, model evaluation, observability, and responsible AI. Builds scalable ML pipelines, conducts experimentation and optimization, and collaborates with Product, Engineering, and business stakeholders to solve complex industrial problems involving forecasting, anomaly detection, demand planning, renewable energy, and predictive maintenance.

Design, build, deploy, and own production AI systems for industrial customers. Engineers implement computational knowledge graphs, replace static workflows with autonomous real-time applications, collaborate directly with operators and stakeholders, deploy systems into high-stakes operational environments, and feed field learnings into platform evolution.

Own the vision, roadmap, and delivery of Avathon’s integrated planning product, including demand forecasting, demand sensing, supply matching, inventory positioning, and S&OP. Translate customer planning needs into reusable product requirements, define AI-enabled planning workflows, and collaborate with engineering, data science, and deployment teams. Drive adoption and measurable customer value through improved forecast accuracy, inventory turns, and planning outcomes.

Lead pre-sales architecture for generative and agentic AI solutions serving industrial customers. Translate business objectives into production-grade architectures using Avathon platforms, hyperscaler services, and OT/IT data systems. Advise executive and technical stakeholders, develop implementation roadmaps, mentor engineering and account teams, lead demonstrations and thought leadership, and establish AI evaluation and monitoring frameworks. The role requires extensive customer-facing experience, AI or machine learning expertise, and 30–50% travel.

Lead the technical delivery of PLM integrations and AI capabilities. Design connectors and data pipelines across PLM, CAD/PDM, ERP, and MES systems; model product structures and engineering changes in a knowledge graph; and build BOM comparison and change-impact services. Lead a small engineering team through customer discovery, implementation, go-live, and hypercare while owning architecture, testing, data validation, security reviews, customer collaboration, and engineering standards.