AI Automation Engineer _ Agentic Builds

Role & responsibilities

• Connect business process to automation. Translate operational workflows into AI-

automation opportunities and identify where agents create the most leverage.

• Process map, then reengineer. Build process maps of current-state workflows and use

them to redesign and reengineer processes for automation not just digitizing the old way

of working.

• 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

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.

• Optimize cost and performance. Make deliberate model-selection and cost-optimization

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

strategies.

• Make it production-ready. Add evaluation, observability, error handling, and guardrails so

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

Preferred candidate profile

• Demonstrated experience building AI agents from scratch not just prompt-tuning or

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

frameworks.

• Strong command of agent orchestration: multi-agent patterns, tool use, retrieval, memory

and state, and coordinating agents within a larger system.

• Hands-on Azure experience deploying services to Azure Container Apps and/or Azure

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

• Proven ability to process-map a workflow and reengineer it for automation, working directly

with business stakeholders to redesign how work gets done.

• Model cost-optimization fluency: choosing the right model for the job, managing token and

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

• Solid software engineering fundamentals — Python and/or TypeScript, APIs, version

control, testing, and CI/CD.

• Comfort operating independently and shipping with minimal oversight in a fast-moving

environment.

Nice to have

• Experience with agent evaluation and observability tooling (eval harnesses, tracing, prompt

and version management).

• Background in management consulting, operations, or business-process reengineering.
• Familiarity with Azure AI services, Azure OpenAI, and broader Azure data and integration

services.

• Experience integrating agents with enterprise systems (CRM, ERP, ticketing, data

warehouses).

• Prior work in a professional-services or client-delivery setting.