Data/ ML Solution Architect

<p><span style="font-size: 16px;">Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses.</span></p> <p> </p> <p><span style="font-size: 16px;">With offices in North America, LATAM, and EMEA, Provectus partners with clients around the world and is obsessed with leveraging cloud, data, and AI to reimagine the way clients operate & compete.</span></p> <p> </p> <p><span style="font-size: 16px;">Position Summary:</span></p> <p><span style="font-size: 16px;"> - As a Solutions Architect, you will be responsible for designing, planning, and implementing scalable, cloud-based, and on-premise data and ML architectures and backend services. </span></p> <p><span style="font-size: 16px;"> - 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. </span></p> <p><span style="font-size: 16px;"> - Your role will focus on delivering high-quality, innovative solutions while adhering to best practices in architecture, security, and compliance. </span></p> <p><span style="font-size: 16px;"> - As a Solutions Architect, you will provide strategic technical leadership on complex, high-impact customer engagements. You will design advanced technical solutions, manage technical risks, and collaborate with cross-functional teams to ensure successful solution delivery. </span></p> <p><span style="font-size: 16px;"> - Your role will involve driving innovation, optimizing customer KPIs, and mentoring other architects and technical leaders. </span></p> <p></p><p><br></p><b>Responsibilities:</b><ul> <li>Lead the design and implementation of data and AI/ML architecture solutions across cloud and on-premise platforms.</li> <li>Lead complex customer engagements, providing strategic technical vision and aligning solutions with customer business goals.</li> <li>Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor.</li> <li>Lead technical workshops, training sessions, and presentations.</li> <li>Define and execute data lifecycle processes: ingestion, storage, processing, and visualization.</li> <li>Collaborate with business units and stakeholders to align solutions with business goals.</li> <li>Ensure solutions adhere to security, compliance, and architecture frameworks (e.g., AWS Well-Architected, GCP Architecture Framework).</li> <li>Lead cross-functional teams, providing mentorship and guidance to technical talent.</li> <li>Design and execute proofs of concept for emerging technologies like Generative AI, Machine Learning</li> <li>Drive backend/ML services best practices for scalable and maintainable solutions.</li> <li>Oversee data governance and data quality processes across platforms.</li> <li>Stay updated with the latest technology trends and continuously improve the architecture strategy.</li> </ul><p><br></p><b>Requirements:</b><ul> <li>7+ years of experience in solutions architecture, with a strong focus on Big Data and cloud platforms (AWS, GCP, Azure).</li> <li>Excellent communication and problem-solving skills, with the ability to work across multiple projects and the ability to articulate complex technical concepts to both technical and non-technical audiences.</li> <li>Technical sales or pre-sales experience with cloud and big data, and ML solutions.</li> <li>Strong leadership and team collaboration abilities.</li> <li>Strategic thinking with a focus on delivering measurable business value.</li> <li>Proven ability to build strong relationships with customers and act as a trusted advisor.</li> <li>Proficiency in data engineering and analytics, designing data pipelines and architectures using AWS, GCP, or Azure data stack.</li> <li>Strong understanding of AI/ML concepts and experience integrating AI/ML components into solutions.</li> <li>Proven experience with data lakes, data warehouses, and real-time data analytics.</li> <li>Proven experience with microservice architecture and containerized deployment options.</li> <li>Hands-on experience with Kubernetes, Docker, and containerized applications.</li> <li>Proficiency in any of backend backend-related languages: TS, Java, Python, and others.</li> <li>Solid understanding of machine learning and MLOps tools (PyTorch, SageMaker, MLFlow).</li> <li>Demonstrated ability to lead and mentor cross-functional teams.</li> <li>Familiarity with agile methodologies.</li> </ul> <div> </div> <div>Nice to Have:</div> <ul> <li>Experience in Generative AI implementations.</li> <li>Proficiency with graph databases (Neo4j, AWS Neptune).</li> <li>Knowledge of data mesh principles and data contracts.</li> <li>Operational knowledge of infrastructure deployment tools like AWS CDK, CloudFormation, and Terraform.</li> </ul><p><br></p><p></p>

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