Lead Architect - Generative AI

Description

• Optimizes AI models for performance and scalability.
• Provides agile methodologies (Scrum, Kanban) and tools like Jira or Trello for project tracking.
• Collaborates with cross-functional teams to integrate AI capabilities into existing systems.
• Provides technical leadership and mentorship to junior team members.
• Designs and develops AI architectures and solutions using AWS and Azure.
• Effectively communicates to bridge technical and non-technical stakeholders, including executives, product managers, and clients.
• Implements infrastructure as code using Terraform.
• Aligns AI initiatives with business goals and drive innovation through generative AI technologies.

Requirements

• Hands-on experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) and tools for model deployment (e.g., Docker, Kubernetes).
• Knowledge of ethical considerations in AI, including bias mitigation, fairness, and compliance with regulations like GDPR or CCPA.
• Excellent problem-solving skills and attention to detail.
• Experience with Terraform for infrastructure automation.
• Customer Centric (internal and/or External)
• Awareness of the latest advancements in generative AI, LLMs (Large Language Models), and multi-modal models.
• Proven ability to manage cross-functional teams, including data scientists, software engineers, and DevOps professionals.
• Familiarity with fine-tuning, prompt engineering, and managing model outputs for scalability and accuracy.
• Remains up to date with the latest advancements in AI and cloud technologies.
• Proficiency in programming languages such as Python, Java, C++, and Net.
• Expertise in designing and integrating RESTful APIs and GraphQL for AI model consumption.
• Proficiency in Python for AI/ML workflows, including libraries like TensorFlow, PyTorch, Hugging Face, and LangChain.
• Bachelor’s degree in Engineering, Computer Science, Information Technology, or a related field and a minimum of 10 years of relevant experience. An equivalent combination of education and experience may be considered.
• Knowledge of machine learning frameworks and libraries.
• Extensive experience with OpenAI APIs (e.g., GPT models, DALL·E, Whisper) and Amazon Bedrock for building and deploying generative AI solutions.
• Strong command of Java for backend development, microservices, or integrating AI models into enterprise systems.
• Master's degree in a related field.
• Experience with AWS (especially Bedrock, SageMaker, Lambda, and S3) and familiarity with other cloud providers like Azure or Google Cloud if needed.
• Experience with other cloud platforms and AI tools.
• Problem-solves to address technical challenges and ensure timely delivery of projects.
• Strong communication and teamwork abilities.
• Familiarity with use cases such as natural language processing (NLP), content generation, chatbots, code generation, and image synthesis.
• Relevant experience with Application Development, Architecture or IT.

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance