AI Engineer & Software Architect
C
CI&TAI Deployment, Tech Solutions
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- Cloud ComputingData engineeringLLMDistributed Systems
Requirements
- Solid experience in AI/ML systems architecture in production or pre-production environments.
- Strong background in distributed systems design, API development, and platform integrations.
- Ability to evaluate trade-offs between 'built vs. buy vs. prototype' solutions.
- Experience with cloud platforms (GCP, AWS, or Azure).
- Expertise in data warehouses/lakes, data pipelines, and feature pipelines.
- Experience integrating with corporate LLM gateways and multi-model proxies (OpenAI, Gemini, Claude).
- Understanding of vector databases and RAG (Retrieval-Augmented Generation) architectures.
- Knowledge of API security (SAST/DAST), data privacy, and compliance (LGPD/GDPR).
- Practice in versioned decision-making (ADR).
- Familiarity with agent orchestration protocols (MCP) and agent-to-agent (A2A) principles.
- Ability to maintain long-term systemic thinking while remaining pragmatic.
- Strong communication skills for interacting with non-technical stakeholders.
Responsibilities
- Design the conceptual architecture of the prototype (PoC) and its path for scalable evolution.
- Evaluate technical and data feasibility alongside the Data Science/AI Engineer.
- Ensure secure integration with existing corporate systems including CRM, behavioral/transactional data platforms, and corporate LLM gateways.
- Apply open standards for agent orchestration (MCP, A2A principles) while avoiding vendor lock-in.
- Document architectural decisions via ADR (Architecture Decision Record) including alternatives and trade-offs.
- Ensure security and data compliance, including PII masking, access control, and decision auditing.
- Collaborate with Data Science, Product, and business specialists to transform validated hypotheses into sustainable architecture.
- Estimate inference costs and scalability feasibility (FinOps) to support Go/No-Go decisions.
- Prepare technical handoffs for delivery teams if the initiative advances to scale.
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