Artificial Intelligence Engineer Em Bahia (ba)

Sky Systems, Inc.; Bahia; Presencial; BRL 167 400 - 223 200; Tempo integral

Resumo da oferta

A Sky Systems, Inc. está em busca de um Engenheiro de Inteligência Artificial para trabalhar 100% remoto a partir da Bahia. O candidato ideal deve ter mais de 8 anos de experiência em engenharia de plataformas e forte conhecimento em integração de ferramentas de inteligência artificial. As responsabilidades incluem promover uma cultura de engenharia centrada em AI, definir métricas de impacto e gerenciar fluxos de trabalho otimização. Oferecemos um ambiente de trabalho colaborativo e dinâmico.

Qualificações

• 8+ anos de experiência em engenharia de plataformas, Dev Ops, ou cargos de engenharia relacionados.
• Experiência prática com APIs LLM e ferramentas de desenvolvedor assistidas por AI.
• Comunicação e gestão de stakeholders excelentes.

Responsabilidades

• Ser o campeão de uma cultura de engenharia com foco em AI.
• Definir e medir impactos usando métricas DORA e SPACE.
• Integrar ferramentas de AI em fluxos de CI/CD e plataformas de desenvolvedor.

Conhecimentos

Experiência em engenharia de plataformas

Desenvolvimento em Python

Trabalho com APIs LLM

Experiência com GitHub Copilot

Gestão de ferramentas AI/SaaS

Ferramentas

Terraform

AWS

GitLab

Helm

Descrição da oferta de emprego

Overview

Artificial intelligence engineer em bahia (BA) – bahia

Requisitos

Job Title: AI Engineer Position Type: Full-Time Contract (40hrs/week) Contract Duration: Long Term Work Schedule:8 hours/day (Mon-Fri) Work Hours: PST Location:100% Remote - (Candidates can work from anywhere in LATAM Countries)

Responsibilities

• Champion an AI-first engineering culture through reusable playbooks, golden-path templates, and best practices that improve developer productivity.
• Define and measure impact using DORA and SPACE metrics, driving improvements across engineering workflows.
• Build reusable patterns for: AI-assisted code generation; Pull request automation; Test generation; Debugging workflows; Developer self-service enablement
• Evaluate, prototype, and lead POCs for AI tools, providing recommendations based on ROI, usability, technical merit, and stakeholder feedback.
• Manage AI usage governance, including: Token budgeting and cost controls; Usage monitoring and reporting; PII redaction guardrails; Audit logging and responsible AI practices
• Develop lightweight AWS-based infrastructure supporting LLM pipelines, APIs, and AI integrations.
• Integrate AI tooling into Git Lab CI/CD, Git Ops workflows, and developer platforms.
• Instrument AI workflows with observability metrics and usage signals to support adoption and optimization.
• Partner with engineering leadership and cross-functional stakeholders to drive AI enablement initiatives.

Qualificações

• 8+ years of experience in Platform Engineering, Dev Ops, Developer Experience, or related engineering roles.
• Strong hands-on experience with LLM APIs and AI-assisted developer tooling in production or enterprise settings.
• Strong Python development skills for automation and AI workflow integrations.
• Experience evaluating, procuring, or governing AI/SaaS tools, including vendor assessments, licensing, and cost management.
• Practical daily usage of tools such as GitHub Copilot, Cursor, Claude Code, ChatGPT, or similar.
• Experience designing scalable developer workflows, internal platforms, or self-service engineering capabilities.
• Strong AWS experience, ideally including: Bedrock API Gateway; Managed AI/Cloud Services.
• Experience with Terraform, Helm, GitOps, and CI/CD pipelines (GitLab preferred).
• Strong observability mindset with experience defining meaningful metrics and instrumentation.
• Excellent communication and stakeholder management skills.
• Preferred / Nice to Have: Experience contributing to an AI Enablement function, Developer Experience program, or Center of Excellence.
• Hands-on experience with: LLM Agents; RAG pipelines; Vector databases (Pinecone, pgvector, Open Search, etc.); LangChain / Llama Index.
• Exposure to AI FinOps, usage reporting, and cost attribution models.
• Knowledge of AI governance and security, including: OWASP Top 10 for LLMs; Prompt injection risks; Model supply chain security; Responsible AI controls.
• Financial services or insurance domain experience is a plus.

Salário

A Combinar

Benefícios

Não informado

Informações adicionais

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