Pessoa Engenheira de Produto de IA Sênior
J
JobgetherAI Engineering
The position is fully remote within Brazil, offering the opportunity to influence products and processes while collaborating with multidisciplinary stakeholders.Full-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- Backend DevelopmentSQLDistributed Systems
Requirements
- Proven experience as a Backend Developer designing and implementing complex APIs and systems.
- Hands-on experience integrating LLMs into real-world applications beyond proofs-of-concept.
- Strong knowledge of complex API orchestration and distributed systems with resilience patterns.
- Experience with RAG, function calling, structured parsing with Pydantic or JSON Schema, and prompt versioning.
- Ability to work with both relational and vector databases and make informed choices between them.
- Experience designing evaluation frameworks for monitoring hallucinations, accuracy, and model quality.
- Ability to design secure data pipelines, including anonymization, access controls, and privacy-conscious integration.
- Strong software engineering fundamentals with the ability to work across backend services and interfaces.
- Experience with vector databases such as Pgvector, Pinecone, or Qdrant.
- Familiarity with corporate integrations like HCM/ERP systems and protocols (SAML, OIDC, SCIM).
- Strong focus on product/business mindset to prioritize tangible operational value.
- Excellent communication skills for collaborating with stakeholders and documenting technical decisions.
Responsibilities
- Conduct shadowing sessions with recruitment, retention, and leadership teams to identify automation opportunities.
- Prioritize operational problems based on business value, technical feasibility, and success metrics.
- Define end-to-end architectures including data sources, LLM approaches, observability, and security.
- Select appropriate technical models and architectures, such as RAG vs. SQL, based on specific problem requirements.
- Develop full-stack AI solutions spanning backend services, LLM integrations, data pipelines, and interfaces.
- Implement robust error handling, circuit breakers, and data anonymization to ensure reliability and security.
- Monitor adoption and performance metrics, creating Evals to assess quality and iterate based on feedback.
- Document architectural decisions and maintain version-controlled prompts as code.
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