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Sr. Software Engineer - AI Platforms and Automation

3 weeks, 4 days ago
United States
Full-time
Senior
AI Engineer
Software Development
Apache Airflow AWS CI/CD Docker Git Kubernetes Machine Learning MLOps PostgreSQL Python Serverless SQL Terraform
Apply Now
Intelligent Medical Objects

Intelligent Medical Objects

IMO is a leading healthcare data enablement company with expertise in clinical terminology and precise data capture at the point of care, empowering informed decisions for improved patient care.

IT Services
251-1K
Founded 1994
View All Jobs 3

Description

  • Maintain and enhance internal applications and tooling for 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 as business needs evolve.
  • Own operational support for AI-enabled production workflows, including troubleshooting, incident response, release coordination, and maintenance.
  • Manage AWS-hosted deployments, infrastructure configuration, monitoring, alerting, and operational support.
  • Investigate production issues, perform root-cause analysis, and implement durable reliability improvements.
  • Support AI agents and workflow automation as they move from pilot efforts to 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 for AI-enabled workflows.
  • Partner with clinical, terminology, product, data science, and engineering teams to improve workflows while maintaining human review and auditability.
  • 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 may be considered.
  • 7+ years of professional experience in software engineering, backend engineering, platform engineering, DevOps, MLOps, cloud engineering, or a related discipline.
  • Experience supporting production systems.
  • Strong proficiency in Python.
  • 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.
  • Hands-on experience with AWS services such as Amazon Bedrock, Lambda, S3, IAM, CloudWatch, Glue, and MWAA/Airflow, 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.
  • Experience with Terraform or Infrastructure-as-Code.
  • Experience with production monitoring and 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 durable solution implementation.
  • 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 (preferred).
  • Experience with modern AI development practices, including tool/function calling, prompt and context engineering, MCP patterns, and AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor (preferred).
  • Experience with AI application frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies (preferred).
  • Experience designing or supporting AI evaluation frameworks, quality monitoring practices, or human-in-the-loop workflows for AI-assisted outputs (preferred).
  • Experience in healthcare technology, clinical data, clinical terminology, content curation, or other regulated data environments (preferred).
  • 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 (preferred).
  • Experience working with vector databases, embeddings, search technologies, or other retrieval-based AI architectures (preferred).
  • AWS certifications such as AWS Certified Solutions Architect, AWS Certified Machine Learning – Specialty, or AWS Certified Generative AI Developer – Professional (preferred).

Interested in this position?

Apply directly on the company website

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