Sr. Software Engineer - AI Platforms & Automation

About the role

IMO Health combines software development, artificial intelligence, and clinical expertise to build AI-driven solutions that improve access to reliable health information, support clinical decision-making, and enhance patient outcomes. We are seeking a Senior Software Engineer to own and evolve the internal platforms that power IMO Health’s terminology and knowledge graph initiatives. This role will maintain and enhance production applications, APIs, integrations, and AI-enabled workflows while introducing new AI capabilities into existing business processes as the platform evolves.

The ideal candidate is a hands-on software engineer who enjoys owning and evolving production software and applying AI technologies to solve real business problems. You will help introduce new AI-enabled capabilities into existing workflows while ensuring underlying systems remain reliable, scalable, and production-ready.

Responsibilities

• Own and enhance internal platforms: Maintain and enhance internally developed applications and tooling for terminology management, content creation, mapping, workflow automation, and content delivery.
• Build and maintain integrations: Develop and maintain integrations across internal applications, APIs, knowledge bases, databases, and AI services.
• Design and implement new automation and AI-enabled capabilities: Contribute to the design and implementation of automation and AI features as business needs evolve.
• Support reliable production systems: Provide operational support for AI-enabled applications and workflows in production, including troubleshooting, incident response, release coordination, and ongoing maintenance.
• Manage deployments and infrastructure: Oversee 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 to improve reliability.
• Enable AI-powered workflows: Support AI agents and workflow automation as they mature from pilot initiatives into scalable production solutions.
• Develop and troubleshoot cloud-based workflows: Build and debug workflows using AWS services such as Bedrock, Lambda, Glue, S3, IAM, CloudWatch, and MWAA/Airflow.
• Implement testing and monitoring: Establish testing, monitoring, and operational readiness practices to 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 human review and auditability.
• Mentor team members: 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 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.

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.

Pay

$140,000 – $200,000 a year. Compensation 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; individual compensation varies accordingly. Figures exclude potential bonuses, equity, or sales incentives, which may also be part of the total compensation package. The recruiter will provide additional details during the hiring process.