Applied AI Solutions Architect
New
P
phDataData and AI
Location: BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years of experience designing, building, or delivering Data, Analytics, Cloud, Software, Machine Learning, or AI solutions.
- Required Skills
- PythonSQLCloud ComputingMachine LearningMLOpsGenerative AI
Requirements
- 8+ years of experience designing, building, or delivering Data, Analytics, Cloud, Software, Machine Learning, or AI solutions.
- At least 5 years of experience designing or leading AI, machine learning, MLOps, or data-intensive solutions in production.
- Hands-on experience with modern cloud, data, and AI ecosystems (e.g., Snowflake, Databricks, AWS, Azure, Google Cloud, dbt, Anthropic, OpenAI).
- Strong proficiency in Python and solid working knowledge of SQL.
- Strong understanding of modern AI patterns such as RAG, semantic retrieval, and agentic architectures.
- Proven ability to translate business requirements into architecture, solution designs, and implementation plans.
- Experience in a consulting, professional services, or client-facing delivery environment.
- Exceptional written and verbal communication, presentation, and facilitation skills.
- Ability to lead technical workstreams and manage multiple priorities effectively.
- Willingness to travel as needed to support customers, workshops, and strategic engagements.
Responsibilities
- Design practical Applied AI solutions spanning predictive machine learning, MLOps, generative AI, and agentic workflows.
- Translate complex business problems into solution designs, technical requirements, and implementation plans.
- Lead technical workstreams and contribute hands-on to prototypes, proofs of concept, and production implementations.
- Collaborate directly with client stakeholders and internal engineering teams to facilitate discovery and roadmap discussions.
- Support sales and senior architects with proposal development, technical demonstrations, and solution shaping.
- Document architecture decisions, tradeoffs, and system interactions while ensuring scalability, security, and observability.
- Contribute to internal practice development by creating reusable accelerators, reference architectures, and standards.
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