We help businesses leverage cloud, data, and AI to reimagine the way they operate, compete, and deliver customer value.
Machine Learning Solution Architect
Location
Colombia
Posted
75 days ago
Salary
0
Seniority
Lead
Job Description
Machine Learning Solution Architect
Provectus
• 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.
Job 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 any of backend 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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