AI Engineer

Aimlroles; Birmingham (AL); Hybrid; USD 120,000 - 160,000; Full time

Job summary

Aimlroles is seeking an AI Engineer to design, build, and operate agent-based AI solutions in a regulated enterprise setting. You will work on end-to-end workflows, integrating models, tools, and enterprise data while adhering to governance and safety standards.

The role emphasizes scalable, observable pipelines, collaboration with ML Ops, and cost-efficient optimization of AI systems across production environments.

Qualifications

• Experience building AI/ML applications in enterprise settings.
• Practical understanding of agentic AI concepts (planners, tool-calling, memory, multi-agent collaboration).
• Familiarity with enterprise data platforms and APIs (structured, unstructured, document-based).
• Awareness of AI governance, risk, and compliance in regulated environments.

Responsibilities

• Develop AI solutions with agents that reason, plan, and act using models, tools, and enterprise data.
• Translate business requirements into end-to-end AI workflows (data ingestion to tool execution).
• Embed safe and explainable AI through guardrails, validation, and prompts.
• Collaborate with architects and ML Ops for deployment, monitoring, and iteration.
• Tune prompts, models, and agent interactions to improve accuracy and cost efficiency.
• Prototype new AI capabilities and push toward enterprise-grade deployments.

Skills

Problem-solving

Communication

Modular agent design

Governance awareness

Tools

Python

Databricks

LLMs & agents

Vector databases

CI/CD

Observability

Job description

AI Engineer

Levels 5-7

Location: The Energy Center, Birmingham, AL or Ivan Allen, Atlanta, GA

4 days in-office / 1 day remote

Designs, builds, and evolves AI solutions that deliver measurable business and operational value across Southern Power. The AI Engineer translates use-case intent into production-ready agents, models, and workflows, working within the enterprise architectural, governance, and operational standards to ensure solutions are scalable, safe, and fit for a critical-infrastructure environment.

JOB REQUIREMENTS: (Experience, Knowledge, Skills)

Domain Expertise

• Experience building AI and machine learning applications in enterprise settings.
• Practical understanding of agentic AI concepts, including planners, tool-calling, memory, and multi-agent collaboration.
• Familiarity with enterprise data platforms and APIs, including structured, unstructured, anddocument-based data.
• Awareness of AI governance, risk, and compliance considerations in regulated environments

Individual Skills:

• Strong problem-solving skills with the ability to decompose complex use cases into modular agentbehaviors.
• Product-oriented mindset, focused on delivering tangible outcomes rather thanexperimentation alone.
• Ability to work effectively within defined architectural and governance constraints.
• Clear communicator who can explain AI behavior and limitations to non-technical stakeholders.

Technical Skills

• Proficiency in Python and AI frameworks for LLMs and agents.
• Proficiency with Databricks preferred.
• Experience with prompt engineering, evaluation techniques, and structured outputs.
• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG)patterns.
• Working knowledge of API integration and tool execution within agent workflows.
• Exposure to CI/CD, model deployment, and observability concepts sufficient to operate within pipelines.

MAJOR JOB RESPONSIBILITIES:

Develop AI solutions. Build and configure agents that reason, plan, andact using models, tools, and enterprise data, aligned to approvedpatterns.

Implement use-case workflows end-to-end. Translate business and operationalrequirements into AI workflows spanning data ingestion, inference, toolexecution, and human-in-the-loop review.

Apply responsible AI and guardrails. Embed safety controls, validation steps,and explainability mechanisms into agent logic and prompts by design.

Collaborate across the AI delivery lifecycle. Partner with architects ondesign decisions and with ML Ops to ensure smooth deployment,monitoring, and iteration.

Optimize performance and cost. Tune prompts, models, and agent interactionsto improve accuracy, latency, and cost efficiency.

Support experimentation to production. Rapidly prototype new AI capabilitieswhile adhering to standards that enable promotion to enterprise-gradedeployments.

Continuously improve agent behavior. Use feedback, evaluations, andoperational signals to refine agent performance and reliability over time

This position falls under the company’s Insider Threat Program and will have access to, and control over sensitive data, systems or assets. Enhanced personnel screening, which includes a background review, drug screen and psychological assessment, will be required if you are selected for this position