Architect

About the Role:

Looking for an experienced AI/ML Architect with 10 years of hands on experience to lead and drive AI and machine learning initiatives across the organization.

The ideal candidate should be capable of owning AI/ML strategy, designing scalable architectures, leading technical teams, and delivering production ready AI solutions across different business domains such as travel, retail, e-commerce, customer experience, operations, analytics, automation, and enterprise productivity.

This role is for someone who can initiate AI/ML programs from scratch, identify business problems where AI can create value, define the right technical approach, guide the team, build prototypes, and take solutions into production.

The candidate should have strong hands on experience in machine learning, cloud ML platforms, vector databases, Generative AI, RAG, AI agents, MCP based integrations, and production grade MLOps.

Required Skills & Qualifications:

10 years of experience in AI/ML, Data Science, AI Engineering, or related technology roles.

Proven experience designing and delivering at least one or more end-to-end AI/ML solutions in production.

• Strong hands-on experience with Python and ML libraries.
• Strong understanding of machine learning algorithms.
• Hands on experience with Generative AI and Agentic AI systems.
• Strong experience with cloud ML platforms, preferably Google Cloud Platform, including Vertex AI, model deployment, cloud data pipelines, and scalable AI services.
• Experience deploying models.
• Good understanding of databases and data platforms.
• Strong Implementation experience of MLOps practices.

Strong architecture mindset with the ability to design AI systems that are scalable, secure, reliable, maintainable, and cost efficient.

Good communication and leadership skills with the ability to guide teams and explain AI/ML solutions to technical and business stakeholders.

Expected Outcomes:

The AI/ML Architect is expected to:

• Define and lead the organization's AI/ML roadmap
• Identify AI opportunities across different business functions
• Build reusable AI/ML platforms, accelerators, and frameworks
• Lead teams from concept to production delivery
• Establish best practices for ML, GenAI, RAG, vector search, agents, and MLOps
• Experience with Google CX Agent/Dialogue Flow CX.
• Deliver production-grade AI systems with measurable business impact
• Improve personalization, forecasting, automation, search, customer experience, and operational efficiency
• Enable faster, safer, and more responsible adoption of AI across the organization.