AI Automation Engineer (Agentic AI - Remote) US, LATAM, Canada

Role Overview

We are hiring a senior independent contractor to design and ship production-grade AI agents that automate real business processes. This is a hands-on building role for someone who lives at the intersection of business-process engineering and applied AI: you will map how work flows today, redesign it around automation, and then build the agents and orchestration that make the new process run.

You will own builds end to end — from process discovery through to agents deployed on Azure (Container Apps and Function Apps) and integrated into the company's broader systems and orchestration layer. You are equally comfortable reasoning about a messy operational workflow and writing the code that automates it, using modern agent-building tooling such as Codex and Claude Code.

Engagement at a Glance

Engagement type: Independent contractor (1099) , full-time

Hours: 40 hours per week

Duration: 3-month term; extension likely based on performance

Location: Remote (U.S. business-hours overlap required)

Initial 3-month term; extension likely based on performance

Remote (U.S. business-hours overlap required)

Reports to: AI Practice Lead

Start: As soon as possible

What You'll Do

automation opportunities and identify where agents create the most leverage.

them to redesign and reengineer processes for automation — not just digitizing the old way of working.

Function Apps, including packaging, configuration, secrets, scaling, and monitoring. • Design for the larger ecosystem. Build agents that fit the company's broader systems and orchestration layer — multi-agent coordination, tool and data integrations, state, and handoffs across the ecosystem.

decisions, balancing capability, latency, and spend across model tiers and routing strategies.

builds are reliable, measurable, and safe to run against real work.

• Connect business process to automation. Translate operational workflows into AI-
• Process map, then reengineer. Build process maps of current-state workflows and use
• Build agents from the ground up. Architect and code agents from scratch using tools such as Codex and Claude Code, with clean, maintainable, testable implementations.
• Ship agentic builds on Azure. Deploy and run agents in Azure Container Apps and Azure
• Optimize cost and performance. Make deliberate model-selection and cost-optimization
• Make it production-ready. Add evaluation, observability, error handling, and guardrails so

What You Bring (Required)

wiring no-code tools — using modern coding agents (e.g., Codex, Claude Code) and agent frameworks.

and state, and coordinating agents within a larger system.

Function Apps (containers, triggers, scaling, configuration, secrets).

with business stakeholders to redesign how work gets done.

compute spend, and tuning for cost, latency, and quality.

control, testing, and CI/CD.

environment.

• Demonstrated experience building AI agents from scratch — not just prompt-tuning or
• Strong command of agent orchestration: multi-agent patterns, tool use, retrieval, memory
• Hands-on Azure experience deploying services to Azure Container Apps and/or Azure
• Proven ability to process-map a workflow and reengineer it for automation, working directly
• Model cost-optimization fluency: choosing the right model for the job, managing token and
• Solid software engineering fundamentals — Python and/or TypeScript, APIs, version
• Comfort operating independently and shipping with minimal oversight in a fast-moving

Nice to Have

and version management).

services.

warehouses).

• Experience with agent evaluation and observability tooling (eval harnesses, tracing, prompt
• Background in management consulting, operations, or business-process reengineering. • Familiarity with Azure AI services, Azure OpenAI, and broader Azure data and integration
• Experience integrating agents with enterprise systems (CRM, ERP, ticketing, data
• Prior work in a professional-services or client-delivery setting.

What Success Looks Like (First 90 Days)

manual process.

orchestration ecosystem.

• Delivered at least one agentic build into production on Azure that automates a previously
• Produced clear current- and future-state process maps that guided the build. • Established a repeatable, cost-aware pattern for standing up new agents within the existing