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.
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.