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Knowledge Graph Engineer Jobs in Chicago, IL (NOW HIRING)

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How much do knowledge graph engineer jobs pay per year?

As of Jul 25, 2026, the average yearly pay for knowledge graph engineer in Chicago, IL is $91,872.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,500.00 and $112,300.00 per year, depending on experience, location, and employer.
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Knowledge Graph Engineer jobs near you
Infographic showing various Knowledge Graph Engineer job openings in Chicago, IL as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 88% Physical, 5% Hybrid, and 7% Remote job distribution, with an average salary of $91,872 per year, or $44.2 per hour.

Sr. Software Engineer - AI Platforms and Automation

IMO Health

Chicago, IL • On-site

$126K - $166K/yr

Full-time

Posted 12 days ago

Job description

At IMO Health, we combine strengths in software development, artificial intelligence, and clinical expertise to create AI-driven solutions that enhance access to reliable health information, support clinical decision-making, and improve patient outcomes. 

We are looking for a Senior Software Engineer to own and evolve the internal software platforms that support IMO Health's terminology and knowledge graph initiatives. This role will maintain and enhance production applications, APIs, integrations, and AI-enabled workflows while helping introduce new AI capabilities into existing business processes as the platform continues to evolve. 

The ideal candidate is a software engineer first-someone who enjoys owning and evolving production software while applying AI technologies to solve real business problems. As the platform continues to evolve, you'll help introduce new AI-enabled capabilities into existing business workflows while ensuring the underlying systems remain reliable, scalable, and production-ready. 

WHAT YOU'LL DO:

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.  

Support reliable production systems 

  • 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.  

Enable AI-powered workflows 

  • 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.  

Collaborate across teams 

  • 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. 

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.

  • Experience building or supporting AI-enabled applications using Amazon Bedrock, LLM APIs, knowledge bases, AI agents, retrieval-augmented generation (RAG), 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.

PREFERRED QUALIFICATIONS:

  • Experience scaling AI-enabled applications or agent-based workflows from prototype or pilot phases into reliable production systems. 

  • Experience with modern AI development practices including prompt engineering, tool/function calling, AI evaluation techniques, and AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor. 

  • Experience with AI application frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies.  

  • Experience designing or supporting AI evaluation frameworks, quality monitoring practices, or human-in-the-loop workflows for AI-assisted outputs. 

  • Experience in healthcare technology, clinical data, clinical terminology, content curation, or other regulated data environments. 

  • Familiarity with knowledge graph technologies and semantic standards such as RDF, OWL, SPARQL, SHACL, FHIR, SNOMED CT, LOINC, RxNorm, ICD-10, CPT, or related healthcare standards. 

  • Experience working with vector databases, embeddings, search technologies, or other retrieval-based AI architectures. 

  • AWS certifications such as AWS Certified Solutions Architect, AWS Certified Machine Learning - Specialty, or AWS Certified Generative AI Developer - Professional. 

$140,000 - $200,000 a year

Compensation at IMO Health is determined by job level, role requirements, and each candidate's experience, skills, and location. The listed base pay represents the target for new hires with individual compensation varying accordingly. These figures exclude potential bonuses, equity, or sales incentives, which may also be part of the total compensation package. Our recruiter will provide additional details during the hiring process.

IMO Health also offers a comprehensive benefits package. To learn more, please visit IMO Health's Careers Page. 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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