With over 12 years of progressive experience, you will drive large-scale, complex AI/ML solutions across Cloud, Data, AI, Work, and Process Modernization journeys utilizing modern Cloud Service Provider (CSP) tech stacks.

This leadership role demands a proven track record of impactful project delivery and exceptional client-facing technical acumen, acting as a trusted advisor to translate intricate engineering concepts into tangible business value and outcomes.

Key Responsibilities :

- Provide strategic leadership and technical oversight for the end-to-end engineering and deployment of large-scale, complex AI/ML solutions, ensuring they demonstrably drive significant business outcomes for clients.

- Lead and manage the architectural design, development, and implementation of robust cloud-native, data-centric, and AI-powered platforms and applications on modern CSP tech stacks.

- Act as a primary client-facing technical lead and trusted advisor, effectively translating complex AI engineering concepts and capabilities into clear, compelling business value propositions for senior stakeholders (CXOs, CTOs).

- Drive business technology and outcome engineering initiatives, focusing on modernizing core processes, workflows, and data strategies through the strategic application of AI.

- Oversee the selection, integration, and optimization of cutting-edge AI/ML frameworks, tools, and services (e.g., LLMs, MLOps platforms, vector databases, specialized AI APIs) to solve complex business challenges.

- Champion DevOps and MLOps best practices to ensure efficient, automated, and reliable deployment, monitoring, and lifecycle management of AI models and applications.

- Collaborate cross-functionally with product management, data science, engineering, and delivery teams to define roadmaps, prioritize initiatives, and ensure alignment with business goals.

- Mentor and grow high-performing AI engineering teams, fostering a culture of innovation, technical excellence, and continuous learning.

- Ensure solutions meet stringent requirements for scalability, performance, security, compliance, and cost-efficiency in cloud environments.

Required Experience/Qualifications :

- 12+ years of progressive experience in business technology and outcome engineering, with a strong focus on Cloud, Data, AI, Work, and Process Modernization journeys on modern Cloud Service Provider (CSP) tech stacks.

- Proven track record of leading the end-to-end engineering and deployment of large-scale, complex AI/ML solutions that demonstrably drove significant business outcomes for clients.

- 8+ years of experience in a client-facing technical lead or principal engineer role, consistently acting as the trusted technical advisor for strategic clients.

- Deep technical expertise in architecting and implementing AI/ML solutions, including machine learning models, natural language processing, computer vision, and generative AI components.

- Extensive experience with cloud platforms (e.g., AWS, Azure, GCP) and their respective AI/ML services and data analytics capabilities.

- Strong understanding of data architectures, data pipelines, and data governance in the context of AI/ML.

- Solid grasp of software engineering best practices, distributed systems, and microservices architectures.

- Excellent communication, presentation, and interpersonal skills, with the ability to articulate complex technical concepts and business value to diverse audiences, including executive leadership.

- Demonstrated ability to translate complex engineering concepts into clear, actionable business value.

- Experience in leading and managing technical teams