Job Description

Position : Google Cloud AI Practice Lead

Location : Pune (Hybrid flexibility for remote work)

Experience : 8 - 11 Years

Company Description :

Evonence is a Google Cloud partner company specializing in providing Google Cloud solutions to mid-market businesses in North America. Founded in 2014, we are one of the fastest-growing partners in the Google Cloud ecosystem. We support a customer base of over 1000 and have deep technical expertise in Google Workspace, Google Cloud infra migrations, and Google Cloud app modernizations.

Role Description :

As a Google Cloud AI Practice Lead at Evonence, you will drive the AI/ML practice, lead solution design, and ensure successful delivery of AI-driven projects on Google Cloud Platform (GCP). This leadership role requires deep expertise in AI/ML technologies, cloud-native architectures, and the ability to engage with stakeholders, mentor teams, and scale the AI practice.

Key Responsibilities (KRAs) :

- Lead the AI/ML practice and define the roadmap for AI initiatives on Google Cloud.

- Architect and design AI/ML solutions leveraging GCP services (Vertex AI, BigQuery ML, TensorFlow, etc.).

- Drive end-to-end project execution from requirement gathering, model development, deployment, and monitoring.

- Collaborate with cross-functional teams to identify business problems and convert them into AI/ML use cases.

- Lead customer engagements, present solutions, and ensure high-quality delivery aligned with client objectives.

- Establish best practices for AI/ML development, model lifecycle management, and responsible AI.

- Mentor and upskill engineers in the AI/ML practice to build strong technical competency.

- Engage in pre-sales activities, proposal building, and solution demonstrations for prospective clients.

- Stay updated with emerging AI technologies, trends, and Google Cloud advancements to maintain competitive advantage.

- Drive thought leadership by creating reference architectures, case studies, and knowledge-sharing sessions.

Required Skillsets

- Strong expertise in AI/ML algorithms, neural networks, pattern recognition, and statistical modeling.

- Proven experience in building and deploying AI/ML solutions on Google Cloud Platform.

- Proficiency in Python and Java for AI/ML development.

- Hands-on experience with ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, and Keras.

- Strong understanding of cloud-native architectures, microservices, and APIs.

- Expertise in data preprocessing, feature engineering, and pipeline automation.

- Knowledge of GCP AI/ML services : Vertex AI, AutoML, BigQuery ML, AI Platform.

- Experience in MLOps practices including CI/CD for ML, model monitoring, and retraining strategies.

- Excellent problem-solving, analytical, and decision-making skills.

- Strong leadership and mentoring capabilities with experience managing technical teams.

- Bachelors degree in Computer Science, Data Science, or related field (Masters preferred).

- Google Cloud Professional ML Engineer or Data Engineer certification is highly desirable.