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Esta oferta expirou em 23/08/2026. Já não aceita candidaturas.

Software Craftsperson – Python & AI (Brazil)

Jobgether

🇬🇧 English
Python TypeScript Prompt engineering LangChain LlamaIndex Pinecone Qdrant PgVector LLMOps CI/CD

Descrição do cargo

About the role

This position sits at the intersection of software engineering and AI‑native development. You will build high‑quality, scalable Python‑based systems while leveraging large language models as co‑creators throughout the software lifecycle.

Key responsibilities

  • Own end‑to‑end delivery of engineering initiatives, ensuring production stability and smooth execution.
  • Design and implement scalable, maintainable features with strong architectural focus.
  • Identify and drive technical, product, and process improvements across teams.
  • Use AI tools to accelerate design, development, testing, debugging, and delivery workflows.
  • Contribute to DevEx and delivery improvements using DORA metrics and flow optimization.
  • Support estimation, planning, and incremental delivery discussions.
  • Provide technical leadership through mentoring and feedback.
  • Collaborate with stakeholders to clarify requirements and align on outcomes.
  • Influence engineering standards, including code quality, testing, and system design.

Required profile

  • 4+ years of software engineering experience.
  • At least 2 years of hands‑on experience with AI/ML systems in production.
  • Strong proficiency in Python (and willingness to work with TypeScript).
  • Experience building production applications using LLMs (e.g., GPT, Claude) for document processing, extraction, or classification.
  • Solid fundamentals in data structures, algorithms, and software design.

Required skills

  • Python
  • TypeScript
  • Prompt engineering and structured output optimization for LLMs
  • LLM orchestration frameworks such as LangChain or LlamaIndex
  • Vector databases (Pinecone, Qdrant, PgVector)
  • LLMOps practices: CI/CD, prompt versioning, evaluation, monitoring, cost optimization
  • Design of scalable backend systems and APIs
  • DORA metrics and flow optimization

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