Artificial Intelligence Specialist

Introduction

Employees in this job function are responsible for developing intelligent programs, cognitive applications, and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants, and specialized programming.

Required Skills & Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
• 3 years of progressive experience in AI/ML, data science, or advanced analytics, with a proven track record of delivering production-grade solutions in large enterprise environments.
• Strong proficiency in Python and SQL. Familiarity with Graph Query Languages (e.g., Cypher).
• Demonstrated experience with MLOps principles and tools (e.g., Azure ML, AWS SageMaker, GCP AI Platform, Kubeflow, MLflow) and designing/implementing AI-specific SDLCs.
• Strong technical expertise in cloud services (GCP/Vertex AI) and data integration patterns.
• Strong analytical, problem-solving, and critical thinking skills.
• Exceptional communication, interpersonal skills, and stakeholder management skills.
• Prior work experience at client or in client's Industry.

Applicants must be able to work directly for Artech on W2.

Preferred Skills & Qualifications

• AI-SDLC Experience: Proven track record of using AI tools to enhance personal or team productivity (e.g., Agentic workflows, RAG-based requirement synthesis).
• Requirement Engineering: Experience in a product engineering role with a proven track record of translating business needs into technical specifications for applied AI implementation.
• Knowledge Graph: Understanding semantic ontologies and how they enable advanced analytics.
• COTS Integration: Experience integrating COTS AI solutions into an enterprise tech stack.
• Supply Chain Domain Knowledge: Functional understanding of supply chain operations, including demand & capacity planning, logistics, sustainability & risk management, resilience, etc.

Day-to-Day Responsibilities

• Understand business requirements and develop AI algorithms, models, and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation, and enable self-service capabilities.
• Perform large-scale experimentation and develop data-driven applications that translate data into actionable intelligence.
• Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants, and specialized programming.
• Research and optimize AI technologies to enhance the efficiency and accuracy of data analysis and create more efficient automation.
• Partner with supply chain functional leads to elicit and document business requirements and translate them into technical specifications for AI-driven decision support tools, ensuring every solution delivers measurable business value.
• Act as the primary technical lead for applied AI implementation. Take pre-developed models from internal partners or 3rd-party vendors (COTS) and successfully deploy them within the supply chain GCP space.
• Work closely with Knowledge Graph engineering teams to map model inputs/outputs to enterprise ontologies. Execute model inference against graph data to provide prescriptions for N-tier supplier risk and material movement.
• Champion and implement AI-assisted development practices. Use LLM-based tools (e.g., GitHub Copilot, automated PR agents, and AI-generated documentation) to accelerate delivery and ensure high code quality.
• Design the "connective tissue" between Knowledge Graph updates and model inference engines. Maintain automated pipelines that ensure decision-support tools are always powered by the most current data.
• Develop reusable integration patterns and data contracts to ensure that AI solutions can be scaled across multiple business units without redundant engineering effort.

For immediate consideration please click APPLY to begin the screening process with Alex.