Senior AI Delivery & Operations Engineer

Jobtailor; Illinois; On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor is seeking an experienced AI software engineer to design, develop, and deploy enterprise AI solutions across the full lifecycle. You will lead delivery squads, build reusable AI factory components, and advance AI quality engineering with automated testing and drift detection.

The role requires deep Python expertise, experience with LLM platforms, and cloud-native deployment in enterprise environments. Collaboration with partners and governance-focused practices are essential.

Qualifications

• Bachelor's degree or equivalent combination of education and relevant experience preferred
• 5+ years of professional software engineering experience required
• Strong expertise in application architecture, API development, testing, source control, CI/CD, deployment automation, and modern software engineering practices
• Hands-on experience designing, developing, deploying, and supporting production AI applications, including post-deployment monitoring, troubleshooting, optimization, and operational support
• Strong proficiency in Python
• Experience building enterprise-grade software solutions using modern development frameworks and engineering best practices
• Experience developing AI solutions utilizing large language models (LLMs) and platforms such as OpenAI, Azure OpenAI, Anthropic, Gemini, or comparable AI technologies
• Experience with cloud-native application development, containerization, infrastructure automation, observability platforms, logging, monitoring, and production support within enterprise environments
• Knowledge of AI engineering concepts including Retrieval-Augmented Generation (RAG), agentic AI, prompt engineering, evaluation frameworks, guardrails, and AI quality engineering preferred
• Experience working within regulated environments supporting data governance, privacy, security, and compliance, preferably within healthcare or similarly regulated industries
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills
• Ability to thrive in fast-paced, highly collaborative, and evolving technical environments

Responsibilities

• Design, develop, test, deploy, and support enterprise AI applications throughout the full AI delivery lifecycle
• Serve as the primary technical contributor for an AI delivery squad and provide technical leadership
• Build and enhance reusable AI Factory capabilities, including shared services, engineering frameworks, implementation patterns, and platform components
• Develop and maintain AI quality engineering capabilities, including automated testing, evaluation frameworks, guardrails, structured outputs, drift detection, failure analysis, and continuous performance optimization
• Support AI Operations (AIOps) and LLMOps through observability, telemetry, logging, monitoring, incident response, root cause analysis, production support, and operational excellence practices
• Contribute to deployment automation, CI/CD pipelines, release management, infrastructure automation, and operational processes
• Collaborate with internal teams and external implementation partners to evaluate technical designs, establish engineering standards, and expand internal AI engineering capabilities through knowledge sharing and mentoring
• Support synthetic data initiatives and AI solutions in regulated healthcare environments using secure, compliant, auditable, and governance-first engineering practices

Skills

Python

API development

CI/CD

Cloud-native

Observability

Automated testing

Data governance

Education

Bachelor's degree or equivalent

Tools

OpenAI

Azure OpenAI

Anthropic

Gemini

Containerization

Logging

Monitoring

Job description

• Design, develop, test, deploy, and support enterprise AI applications, agentic workflows, retrieval-augmented generation (RAG) solutions, and model-powered APIs throughout the full AI delivery lifecycle
• Serve as the primary technical contributor for an AI delivery squad and provide technical leadership
• Build and enhance reusable AI Factory capabilities, including shared services, engineering frameworks, implementation patterns, and platform components
• Develop and maintain AI quality engineering capabilities, including automated testing, evaluation frameworks, guardrails, structured outputs, drift detection, failure analysis, and continuous performance optimization
• Support AI Operations (AIOps) and LLMOps through observability, telemetry, logging, monitoring, incident response, root cause analysis, production support, and operational excellence practices
• Contribute to deployment automation, CI/CD pipelines, release management, infrastructure automation, and operational processes
• Collaborate with internal teams and external implementation partners to evaluate technical designs, establish engineering standards, and expand internal AI engineering capabilities through knowledge sharing and mentoring
• Support synthetic data initiatives and AI solutions in regulated healthcare environments using secure, compliant, auditable, and governance-first engineering practices

Requirements

• Bachelor's degree or equivalent combination of education and relevant experience preferred
• 5+ years of professional software engineering experience required
• Strong expertise in application architecture, API development, testing, source control, CI/CD, deployment automation, and modern software engineering practices
• Hands-on experience designing, developing, deploying, and supporting production AI applications, including post-deployment monitoring, troubleshooting, optimization, and operational support
• Strong proficiency in Python
• Experience building enterprise-grade software solutions using modern development frameworks and engineering best practices
• Experience developing AI solutions utilizing large language models (LLMs) and platforms such as OpenAI, Azure OpenAI, Anthropic, Gemini, or comparable AI technologies
• Experience with cloud-native application development, containerization, infrastructure automation, observability platforms, logging, monitoring, and production support within enterprise environments
• Knowledge of AI engineering concepts including Retrieval-Augmented Generation (RAG), agentic AI, prompt engineering, evaluation frameworks, guardrails, and AI quality engineering preferred
• Experience working within regulated environments supporting data governance, privacy, security, and compliance, preferably within healthcare or similarly regulated industries
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills
• Ability to thrive in fast-paced, highly collaborative, and evolving technical environments

Core Competencies

Demonstrates expertise in designing, developing, and supporting enterprise AI applications and solutions, with a strong focus on API development, deployment automation, and AI quality engineering. Proficient in collaborating with cross-functional teams to enhance AI capabilities while ensuring compliance in regulated environments.

Highest-signal resume keywords

• AI Application Development
• Python Proficiency
• CI/CD Pipeline Management
• Cloud-Native Application Development
• AI Quality Engineering

ATS Optimization Keywords

Hard Skills

• Application Architecture
• API Development
• Deployment Automation
• Automated Testing
• Observability
• Drift Detection
• Failure Analysis
• Continuous Performance Optimization
• Large Language Models (LLMs)
• Infrastructure Automation

Soft Skills

• Analytical Skills
• Problem-Solving
• Communication
• Cross-Functional Collaboration

Industry Keywords

• Regulated Environments
• Data Governance
• Privacy
• Security
• Compliance
• Healthcare

Tools & Technologies

• OpenAI
• Azure OpenAI
• Anthropic
• Gemini
• Containerization
• Logging
• Monitoring