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About This Role
At IMO Health, we combine strengths in software development, artificial intelligence, and clinical expertise to create AI\-driven solutions that enhance access to reliable health information, support clinical decision\-making, and improve patient outcomes.
We are looking for a Sr. Software Engineer to own and evolve the internal software platforms that support IMO Health's terminology and knowledge graph initiatives. This role will maintain and enhance production applications, APIs, integrations, and AI\-enabled workflows that help teams create, manage, and deliver high\-quality clinical data.
The ideal candidate is a strong software engineer who enjoys owning complex systems, improving reliability, and partnering across technical and business teams to evolve AI\-enabled solutions.
### WHAT YOU’LL DO:
Own and enhance internal platforms
- 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.
Support reliable production systems
- 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.
Enable AI\-powered workflows
- 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.
Collaborate across teams
- 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.
### WHAT YOU’LL NEED:
- 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, including hands\-on experience with services such as Amazon Bedrock, Lambda, S3, IAM, CloudWatch, Glue, 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, 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.
- 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 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 tool/function calling, prompt and context engineering, MCP patterns, 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.
$140,000 \- $200,000 a year
Compensation at IMO Health 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 with individual compensation varying accordingly. These figures exclude potential bonuses, equity, or sales incentives, which may also be part of the total compensation package. Our recruiter will provide additional details during the hiring process.
IMO Health also offers a comprehensive benefits package. To learn more, please visit IMO Health's Careers Page.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Salary Context
This $140K-$200K range is below the median for AI Software Engineer roles in our dataset (median: $183K across 194 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Intelligent Medical Objects, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $219,250 based on 424 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($170K) sits 22% below the category median. Disclosed range: $140K to $200K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Intelligent Medical Objects AI Hiring
Intelligent Medical Objects has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Chicago, IL, US. Compensation range: $200K - $200K.
Location Context
AI roles in Chicago pay a median of $205,100 across 97 tracked positions. That's 6% below the national median.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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