AI Architect - GenAI Solutions

About the role

Arrow Electronics is hiring an AI Architect in Bangalore to design, develop and implement AI and GenAI solutions that turn complex business problems into innovation. The role bridges business objectives and technology, ensuring AI systems align with the organization's strategy. It is a full-time position.

Key responsibilities

• Define and design AI architecture, frameworks and strategies, and evaluate and select AI tools and platforms.
• Supervise or contribute to the development, training and optimization of large and small language models.
• Integrate AI solutions with existing business processes in line with internal policies and stay up to date on AI advances.
• Design scalable, secure and maintainable AI solutions, and collaborate with external vendors and partners.
• Plan and execute projects: define scope, goals and deliverables, build detailed plans and timelines, and set KPIs for ROI.
• Manage day-to-day activities, anticipate risks such as data limitations or algorithm performance issues, and ensure compliance with data privacy, industry standards and ethical guidelines.
• Act as the main liaison between AI research teams, data scientists, engineers, product managers and business stakeholders, and coordinate work between onsite and offshore teams.

Required profile

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science or a related field (advanced degree preferred).
• Minimum 5 years of experience in AI projects, data science or a related field.
• Proven experience managing technical projects, preferably in AI, machine learning or data-driven technologies.
• Ability to manage multiple projects and prioritize, with strong problem-solving, analytical and communication skills.

Required skills

• AI and GenAI technologies, including supervised/unsupervised learning, deep learning, NLP and computer vision.
• Programming in Python and .NET.
• Cloud technologies (Azure and GCP), APIs and microservices.
• Big data tools such as Hadoop and Apache Spark.
• Tools such as Azure AI Foundry, Ollama and DataBricks.
• Agile methods and tools such as Jira and Trello.
• Knowledge of AI ethics and regulatory compliance, and of data engineering and cloud architecture principles.