AI Architect (EA100FT RM 3966)

Position: AI Architect (EA100FT RM 3966)

Job Description:
A highly skilled and motivated AI Architect for designing, developing, and implementing artificial intelligence (AI) solutions within an organization. The role focuses on leveraging AI & GenAI technologies, machine learning (ML), natural language processing (NLP), computer vision, and predictive analytics to solve complex business problems and drive innovation. The AI Architect bridges the gap between business objectives and technology, ensuring that AI systems align with the organization’s strategic goals.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Advanced degree preferred.
• Experience: Minimum of 5 years of experience in AI projects, data science, or a related field.

Skills:
o Expertise in AI & GenAI technologies, frameworks, and methodologies (e.g., supervised/unsupervised learning, deep learning, NLP, computer vision).
o Proficiency in programming languages like Python, .Net
o Strong understanding of cloud technologies (Azure & GCP), APIs, and microservices.
o Proven experience in managing technical projects, preferably in AI, machine learning, or data-driven technologies.
o Knowledge of big data processing tools (e.g., Hadoop, Apache Spark).
o Hands on experience with tools and platforms used in AI development (e.g., Azure AI Foundry, Ollama, DataBricks etc.).
o Experience in architecting AI Solutions using on premise and Cloud technologies.
o Experience with agile methodologies and tools (e.g., Jira, Trello) for managing technical projects.
o Demonstrated ability to manage multiple projects simultaneously and prioritize effectively.
o Strong problem-solving, analytical, and communication skills.
o Knowledge of AI ethics and regulatory compliance frameworks.
o Proficiency with data engineering and cloud architecture principles.

Key Responsibilities
Technical Expertise

• Define and design AI architecture, frameworks, and strategies to meet organizational needs.
• Evaluate and select AI tools, platforms, and frameworks to develop innovative solutions.
• Supervise or contribute to the development, training, and optimization of Large as well as small language models.
• Ensure seamless integration of AI solutions with existing business processes while ensuring that the solution complies with Arrow’s internal policies and guidelines.
• Design AI solutions that are scalable, secure, and maintainable over time.
• Stay updated on the latest advancements in AI and machine learning to propose innovative solutions.
• Strong understanding & knowledge about Microsoft Azure cloud and deploying PaaS & SaaS applications on Azure
• Strong architecture background especially in AI Solutions and Cloud technologies.
• Collaborate with external vendors and partners to leverage their expertise and solutions.

Project Planning and Execution

• Define project scope, goals, and deliverables that align with business objectives.
• Develop detailed project plans, timelines, and milestones for AI development and deployment initiatives for the inhouse GenAI platform.
• Collaborate with business units for ROI determination and identify KPI’s for measuring ROI for each project.
• Manage day-to-day project activities to ensure successful execution and timely delivery.
• Anticipate potential risks and challenges in AI projects (e.g., data limitations, algorithm performance issues, regulatory concerns).
• Proactively implement risk mitigation strategies and contingency plans.
• Ensure that AI projects comply with data privacy regulations, industry standards, and ethical guidelines.
• Promote responsible use of AI technologies across all projects.

Team Collaboration and Coordination

• Act as the primary liaison between AI research teams, data scientists, engineers, product managers, and business stakeholders.
• Facilitate regular meetings and communications between business units and IT to discuss AI project progress, challenges, and opportunities.
• Plan and coordinate work between onsite and offshore AI teams.
• Foster collaboration among team members and remove obstacles to productivity.

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