WHAT WE’RE LOOKING FOR

• 10+ years of experience in technology, with at least 5 years in AI/ML solution architecture and delivery.
• Proven record of designing and implementing AI solutions that have driven tangible business outcomes.
• Strong knowledge of AI/ML frameworks (TensorFlow, PyTorch, scikit-learn) and modern MLOps practices.
• Hands-on expertise with cloud-based AI services (AWS, Azure, GCP).
• Understanding of ethical AI practices, governance, and responsible AI design.
• Excellent communication and stakeholder management skills, with the ability to bridge business needs and technical solutions.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

ROLE OVERVIEW

We are looking for an experienced Senior AI Architect to help shape and expand our AI-driven initiatives. In this role, you’ll define end-to-end AI architectures, guide clients in leveraging AI to solve complex business challenges, and act as a trusted advisor both internally and externally. You’ll also serve as a thought leader, helping to advance our brand’s reputation in the broader technology ecosystem.

WHAT YOU’LL DO

• Architect AI Solutions: Design and implement AI systems that create measurable business value across domains such as predictive analytics, generative AI, computer vision, natural language processing, and automation.
• Engage with Clients: Work closely with business and technical stakeholders to identify opportunities, frame AI use cases, and lead the design process.
• Establish Standards: Define frameworks, best practices, and architectural guidelines for AI projects to ensure scalable and sustainable delivery.
• Support Growth: Contribute to pre-sales and sales engagements by clearly communicating the value and impact of AI solutions to executives and technical teams.
• Mentor and Enable: Guide internal teams, build organizational capabilities in AI/ML, and foster knowledge-sharing across global teams.
• Leverage Advanced AI Tools: Apply state-of-the-art approaches including large language models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents. Experience with frameworks such as LangChain, LlamaIndex, and cloud-based deployment (AWS, Azure, GCP) is essential.
• Hands-On Delivery: Develop, fine-tune, and deploy machine learning models across multiple use cases, including image, language, and recommendation systems.
• Optimize Performance: Demonstrated expertise in writing/tuning LLM prompts and familiarity with tools like Microsoft PromptFlow and RAG evaluation methods.