Provectus is a Premier AWS partner at the forefront of Artificial Intelligence solutions. We empower businesses to unlock value and accelerate their transformation via bespoke applications, managed services, and advisory engagements. We operate in North America, LATAM, and EMEA, partnering with clients around the world. Our focus is on leveraging cloud, data, and AI to reimagine the way clients operate & compete. Job Summary: - This role involves designing, planning, and implementing scalable, cloud-based, and on-premise data and ML architectures and backend services. - You will collaborate with internal teams, clients, and stakeholders to build state-of-the-art solutions across Big Data, machine learning, and real-time analytics environments. - Your role will focus on delivering high-quality, innovative solutions while adhering to best practices in architecture, security, and compliance. Key Responsibilities: - Lead the design and implementation of data and AI/ML architecture solutions across cloud and on-premise platforms. - Provide strategic technical vision and align solutions with customer business goals during complex customer engagements. - Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor. - Design and execute data lifecycle processes: ingestion, storage, processing, and visualization. - Collaborate with business units and stakeholders to ensure solutions align with business goals. - Evaluate and enforce adherence to security, compliance, and architecture frameworks. - Lead cross-functional teams, providing mentorship and guidance to technical talent. - Stay updated with the latest technology trends and continuously improve the architecture strategy. Requirements: - 7+ years of experience in solutions architecture, focusing on Big Data and cloud platforms (AWS, GCP, Azure). - Excellent communication and problem-solving skills for articulating complex technical concepts to both technical and non-technical audiences. - Technical sales or pre-sales experience with cloud and big data, and ML solutions. - Strong leadership and team collaboration abilities. - Proficiency in data engineering and analytics, designing data pipelines and architectures using AWS, GCP, or Azure data stack. - Experience integrating AI/ML components into solutions. - Proven experience with data lakes, data warehouses, and real-time data analytics. - Familiarity with agile methodologies. The ideal candidate will have hands-on experience with Kubernetes, Docker, and containerized applications, along with proficiency in backend-related languages such as TS, Java, Python, and others. A solid understanding of machine learning and MLOps tools (PyTorch, SageMaker, MLFlow) is also necessary. Demonstrated ability to lead and mentor cross-functional teams is a must.