Artificial Intelligence Engineer

Artificial Intelligence Engineer - Detalhes da Vaga. ● 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. ●The ideal candidate will bring hands-on experience with LLM APIs, AI developer tooling, Python automation, cloud infrastructure, and developer productivity metrics, while helping shape internal AI governance, adoption frameworks, and scalable engineering golden paths. ●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- 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- 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, OpenSearch, etc. ●)- LangChain / LlamaIndex- 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. ●. Requisitos para participar do processo. ● . O que oferecemos.