Sr. Software Engineer - AI Automation

Job Description

Requirements
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### Must have:

### - We require a bachelors or masters degree in Computer Science, Software Engineering, Data Engineering, Machine Learning, or a closely related technical field, although comparable professional experience may be considered. - We look for 7+ years of professional experience in software engineering, backend engineering, platform engineering, DevOps, MLOps, cloud engineering, or a similar discipline, including hands-on support for production systems. - We need strong Python expertise and experience building dependable services, APIs, internal tools, batch jobs, or workflow automation in production. - We expect experience designing, deploying, and supporting cloud applications in AWS. - We require experience building or supporting AI-enabled applications with Amazon Bedrock, LLM APIs, knowledge bases, AI agents, retrieval-augmented generation (RAG), or comparable technologies. - We look for experience with CI/CD pipelines, Git-based development practices, automated testing, configuration management, and release processes. - We require experience with Docker, Kubernetes or similar containerized platforms, Terraform or Infrastructure-as-Code, and production monitoring/alerting tools. - We expect experience with workflow orchestration, data pipelines, or scheduling tools such as Airflow/MWAA, Glue, Lambda, cron-based jobs, or equivalent solutions. - We need working knowledge of SQL and relational databases such as PostgreSQL; experience with distributed data or search platforms is a plus. - We require strong troubleshooting skills, including production incident triage, root-cause analysis, log review, and implementation of lasting fixes. - We need the ability to collaborate effectively with subject matter experts and translate workflow requirements into practical, maintainable technical solutions. - We require strong communication, documentation, and cross-functional collaboration skills. - Preferred qualifications include experience scaling AI-enabled applications or agent-based workflows from prototype or pilot into production. - Preferred qualifications include experience with prompt engineering, tool/function calling, AI evaluation methods, and AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor. - Preferred qualifications include experience with AI application frameworks such as LangChain, LangGraph, LlamaIndex, or similar tools. - Preferred qualifications include experience designing or supporting AI evaluation frameworks, quality monitoring practices, or human-in-the-loop workflows. - Preferred qualifications include experience in healthcare technology, clinical data, clinical terminology, content curation, or other regulated data environments. - Preferred qualifications include familiarity with knowledge graph technologies and semantic standards such as RDF, OWL, SPARQL, SHACL, FHIR, SNOMED CT, LOINC, RxNorm, ICD-10, and CPT. - Preferred qualifications include experience with vector databases, embeddings, search technologies, or other retrieval-based AI architectures. - Preferred qualifications include AWS certifications such as AWS Certified Solutions Architect, AWS Certified Machine Learning - Specialty, or AWS Certified Generative AI Developer - Professional.

Responsibilities:
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- We maintain and enhance internal applications and tooling that support terminology management, content creation, mapping, workflow automation, and content delivery. - We build and sustain integrations across internal applications, APIs, knowledge bases, databases, and AI services. - We contribute to the design and rollout of new automation and AI-enabled capabilities as business needs change. - We own operational support for AI-enabled production applications and workflows, including troubleshooting, incident response, release coordination, and ongoing maintenance. - We manage deployments, infrastructure configuration, monitoring, alerting, and operational support for AWS-hosted applications and services. - We investigate production issues, perform root-cause analysis, and implement durable improvements to reliability. - We support AI agents and workflow automation capabilities as they mature into scalable production solutions. - We develop and troubleshoot cloud-based workflows using AWS services such as Bedrock, Lambda, Glue, S3, IAM, CloudWatch, and MWAA/Airflow. - We implement testing, monitoring, and operational readiness practices that improve the quality and dependability of AI-enabled workflows. - We partner with clinical, terminology, product, data science, and engineering teams to improve AI-enabled workflows while maintaining human review and auditability. - We mentor team members and promote engineering best practices for secure, maintainable, production-ready systems.
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Company:
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At IMO Health, we combine software development, artificial intelligence, and clinical expertise to build AI-driven solutions that improve access to reliable health information, support clinical decision-making, and help deliver better patient outcomes. This Senior Software Engineer role is focused on owning and evolving our internal platforms that power terminology and knowledge graph initiatives, while also introducing new AI capabilities into existing business processes. You will work on production applications, APIs, integrations, and cloud-based workflows in an environment that values reliability, scalability, and practical innovation. We offer a comprehensive benefits package, and compensation is targeted at $140,000 to $200,000 per year, with final pay based on role level, experience, skills, and location.
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