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Responsibilities
Lead the design and implementation of data and AI/ML architecture solutions across cloud and on-premise platforms
Lead complex customer engagements, providing strategic technical vision and aligning solutions with customer business goals
Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor
Lead technical workshops, training sessions, and presentations
Define and execute data lifecycle processes: ingestion, storage, processing, and visualization
Collaborate with business units and stakeholders to align solutions with business goals
Ensure solutions adhere to security, compliance, and architecture frameworks (e.g., AWS Well-Architected, GCP Architecture Framework)
Lead cross-functional teams, providing mentorship and guidance to technical talent
Design and execute proofs of concept for emerging technologies like Generative AI, Machine Learning
Drive backend/ML services best practices for scalable and maintainable solutions
Oversee data governance and data quality processes across platforms
Stay updated with the latest technology trends and continuously improve the architecture strategy
Requirements
7+ years of experience in solutions architecture, with a strong focus on Big Data and cloud platforms (AWS, GCP, Azure)
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
Technical sales or pre‐sales experience with cloud and big data, and ML solutions
Strong leadership and team collaboration abilities
Strategic thinking with a focus on delivering measurable business value
Proven ability to build strong relationships with customers and act as a trusted advisor
Proficiency in data engineering and analytics, designing data pipelines and architectures using AWS, GCP, or Azure data stack
Strong understanding of AI/ML concepts and experience integrating AI/ML components into solutions
Proven experience with data lakes, data warehouses, and real‐time data analytics
Proven experience with microservice architecture and containerized deployment options
Hands‐on experience with Kubernetes, Docker, and containerized applications
Proficiency in backend‐related languages: TS, Java, Python, and others
Solid understanding of machine learning and MLOps tools (PyTorch, SageMaker, MLFlow)
Demonstrated ability to lead and mentor cross‐functional teams
Familiarity with agile methodologies
Nice to Have
Experience in Generative AI implementations
Proficiency with graph databases (Neo4j, AWS Neptune)
Knowledge of data mesh principles and data contracts
Operational knowledge of infrastructure deployment tools like AWS CDK, CloudFormation, and Terraform
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Postúlate en Kit Empleo: kitempleo.com.co/empleo/1asw1b

📌 Data/ Ml Solution Architect (Genai, Aws) (Valle del Cauca)
🏢 Provectus
📍 Valle del Cauca