IMO Health combines strengths in software development, artificial intelligence, and clinical expertise to create AI-driven solutions. They are seeking a Senior Software Engineer to own and evolve internal software platforms that support terminology and knowledge graph initiatives, maintaining and enhancing production applications while introducing new AI capabilities.

Responsibilities:

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:

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
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
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

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