Note: The job is a remote job and is open to candidates in USA. 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
Skills
- 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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