Senior Software Engineer – AI Platforms and Automation

Intelligent Medical Objects (IMO)

Sr. Software Engineer developing internal software platforms for AI-driven health solutions at IMO Health.

Posted 7/15/2026full-timeRemote • Illinois, Texas • 🇺🇸 United StatesSenior💰 $140,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and maintaining cloud-based applications and workflows, particularly within AWS environments, while ensuring operational support and reliability of AI-enabled systems. Proficient in Python and experienced in implementing automation, CI/CD practices, and collaborating with cross-functional teams to enhance internal platforms.

Highest-signal resume keywords

AWS Application DevelopmentPython ProficiencyCI/CD Pipeline ImplementationAI-Enabled Application SupportWorkflow Automation

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonAWS ServicesCI/CD PipelinesDockerKubernetesTerraformSQLAirflow/MWAAGlueProduction Monitoring

Soft Skills

Strong CommunicationCollaborationTroubleshootingDocumentationMentoring

Tools & Technologies

Amazon BedrockLambdaS3IAMCloudWatchGitConfiguration ManagementLog AnalysisIncident ResponseProduction Support

Industry Keywords

Software EngineeringPlatform EngineeringDevOpsMLOpsCloud EngineeringWorkflow OrchestrationData PipelinesAI AgentsTerminology ManagementContent Delivery

Tech Stack

Tools & technologies

AirflowAWSCloudDockerKubernetesPostgresPythonSQLTerraform

About the role

Key responsibilities & impact

Own and enhance internal platforms
Maintain and enhance internally developed applications and tooling that supports terminology management, content creation, mapping, workflow automation, and content delivery.
Build and maintain integrations across internal applications, APIs, knowledge bases, databases, and AI services.
Contribute to the design and implementation of new automation and AI-enabled capabilities as business needs evolve.
Own operational support for AI-enabled applications and workflows in production, including troubleshooting, incident response, release coordination, and ongoing maintenance.
Manage application deployments, infrastructure configuration, monitoring, alerting, and operational support for AWS-hosted applications and services.
Investigate production issues, perform root-cause analysis, and implement durable solutions that improve reliability.
Support AI agents and workflow automation capabilities as they mature from pilot initiatives into scalable production solutions.
Develop and troubleshoot cloud-based workflows using AWS services such as Bedrock, Lambda, Glue, S3, IAM, CloudWatch, and MWAA/Airflow.
Implement testing, monitoring, and operational readiness practices that improve the quality and reliability of AI-enabled workflows.
Partner with clinical, terminology, product, data science, and engineering teams to improve AI-enabled workflows while maintaining appropriate human review and auditability.
Mentor team members and promote software engineering best practices for secure, maintainable, and production-ready systems.

Requirements

What you’ll need

Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Machine Learning, or a related technical field; equivalent professional experience will also be considered.
7+ years of professional experience in software engineering, backend engineering, platform engineering, DevOps, MLOps, cloud engineering, or a related discipline, including experience supporting production systems.
Strong proficiency in Python and experience building maintainable services, APIs, internal tools, jobs, or workflow automation in production environments.
Experience designing, deploying, and supporting cloud-based applications in AWS environments, including hands-on experience with services such as Amazon Bedrock, Lambda, S3, IAM, CloudWatch, Glue, MWAA/Airflow, or similar technologies.
Experience with CI/CD pipelines, Git-based development workflows, automated testing, configuration management, and release practices.
Experience with Docker, Kubernetes or other containerized services, Terraform or Infrastructure-as-Code, and production monitoring/alerting tools.
Experience with workflow orchestration, data pipelines, or job scheduling tools such as Airflow/MWAA, Glue, Lambda, cron-based jobs, or equivalent technologies.
Working knowledge of SQL and relational databases such as PostgreSQL; experience with distributed data or search systems is a plus.
Experience building or supporting AI-enabled applications using LLM APIs, retrieval-augmented generation (RAG), knowledge bases, AI agents, or similar technologies.
Strong troubleshooting skills, including production issue triage, root-cause analysis, log analysis, and implementation of durable solutions.
Ability to partner effectively with domain experts and translate workflow needs into practical, maintainable technical solutions.
Strong communication, documentation, and collaboration skills in cross-functional environments.

Benefits

Comp & perks

Comprehensive benefits package
Potential bonuses, equity, or sales incentives