Senior Software Engineer – AI Platforms, Automation

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Intelligent Medical Objects (IMO)

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 1993

🏥 Healthcare

💼 Consulting

📦 Logistics

💰 Venture Round on 2017-02

Healthcare • Consulting • Logistics

Intelligent Medical Objects (IMO) is a leader in transforming healthcare data by employing AI and rich medical terminology. With over 30 years in the field, IMO specializes in clinical terminology, coding, and mapping. They serve healthcare providers, life sciences, public health, and health information exchanges, among others. Their solutions enhance data quality management, standardize procedures, and unlock insights from clinical data through AI. Trusted by 98% of academic medical centers, IMO's products are pivotal in improving patient care, surgical scheduling, OR efficiency, and precision data management.

📋 Description

• Own and enhance internally developed applications and tooling supporting terminology management, content creation, mapping, workflow automation, and content delivery • Build and maintain integrations across internal applications, APIs, knowledge bases, databases, and AI services • Design and implement new automation and AI-enabled capabilities • Provide operational support for AI-enabled applications and workflows in production, including troubleshooting, incident response, release coordination, and maintenance • Manage deployments, infrastructure configuration, monitoring, alerting, and operational support for AWS-hosted applications and services • Investigate production issues, perform root-cause analysis, and implement durable reliability improvements • Support AI agents and workflow automation capabilities as they mature into scalable production solutions • Develop and troubleshoot AWS cloud workflows using Bedrock, Lambda, Glue, S3, IAM, CloudWatch, and MWAA/Airflow • Implement testing, monitoring, and operational-readiness practices for AI-enabled workflows • Partner with clinical, terminology, product, data science, and engineering teams • Mentor team members and promote secure, maintainable, production-ready engineering practices

🎯 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 production systems support • Strong proficiency in Python and experience building maintainable production services, APIs, internal tools, jobs, or workflow automation • Experience designing, deploying, and supporting cloud-based applications in AWS • Experience building or supporting AI-enabled applications using Amazon Bedrock, LLM APIs, knowledge bases, AI agents, 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 • Strong troubleshooting skills, including production issue triage, root-cause analysis, log analysis, and durable solutions • Ability to partner with domain experts and translate workflow needs into practical technical solutions • Strong communication, documentation, and collaboration skills • Preferred: experience scaling AI applications or agent-based workflows into production • Preferred: prompt engineering, tool/function calling, AI evaluation, and AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor • Preferred: LangChain, LangGraph, LlamaIndex, healthcare technology, clinical data, clinical terminology, regulated data environments, knowledge graphs, semantic standards, vector databases, embeddings, and search technologies • Preferred: AWS certifications

🏖️ Benefits

• Base pay target of $140,000–$200,000 per year • Potential bonuses • Equity • Comprehensive benefits package