Artificial Intelligence Engineer Em São Luís (ma)

Sky Systems, Inc.; Maranhão; Presencial; BRL 398 009 - 597 014; Tempo integral

Resumo da oferta

Sky Systems, Inc. is seeking an experienced AI Engineer to integrate AI tooling into software development processes. The ideal candidate will champion AI-first engineering practices and drive improvements across engineering workflows. Applicants should have over 8 years of experience in relevant engineering roles and strong hands-on experience with LLM APIs. This position is fully remote, allowing candidates to work from anywhere in LATAM. Salary is flexible and based on experience.

Qualificações

• Experience with AI-assisted developer tooling in production settings.
• Experience designing scalable developer workflows.
• Practical usage of LLM tools like ChatGPT, Claude Code.

Responsabilidades

• Champion an AI-first engineering culture to improve productivity.
• Build reusable patterns for AI-assisted code generation.
• Integrate AI tooling into GitLab CI/CD workflows.

Conhecimentos

8+ years in Platform Engineering or DevOps

Strong hands-on with LLM APIs

Python development skills

Experience with GitHub Copilot

Strong AWS experience

Excellent communication skills

Ferramentas

AWS

GitLab CI/CD

Descrição da oferta de emprego

Cargo

Artificial intelligence engineer em são luís (MA) – são luís

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

Overview

We are seeking an experienced AI Engineer to drive AI‑first engineering practices and enable developer productivity at scale. This role sits at the intersection of Developer Experience, Platform Engineering, DevOps, and Applied AI, focused on integrating AI‑assisted tooling, LLM workflows, and automation into the software development lifecycle.

Key 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, and 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 GitLab CI/CD, GitOps 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.

Required Qualifications

• 8+ years of experience in Platform Engineering, DevOps, 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, 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, OpenSearch, etc.), LangChain / Llama Index.
• Exposure to AI financial operations, 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, and responsible AI controls.
• Financial services or insurance domain experience.

Salário

A Combinar