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Informatics Software Engineer Jobs (NOW HIRING)

Predicine

$150 - $200/hr

Software Engineer (Production Informatics) Full Time Professional Hayward, CA, US Software Engineer, Production Informatics About Predicine Predicine is a precision oncology company advancing the ...

Prime Medicine, Inc.

$125 - $150/hr

About the role We\'re hiring an Informatics Engineer to build the scientific data and computing ... Translate scientific requirements into reliable, maintainable software, helping bring research ...

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Informatics Software Engineer information

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$63.5K

$147.5K

$205.5K

How much do informatics software engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for informatics software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What is an informatics software engineer?

An Informatics Software Engineer is a professional who develops and maintains software systems that manage, analyze, and interpret data within the field of informatics. This role often involves working with healthcare, biological, or research data, ensuring that information is efficiently processed and integrated. Informatics Software Engineers collaborate with data scientists, researchers, and other IT professionals to design tools that support data-driven decision-making. Their work helps organizations leverage complex data for improved outcomes and innovation.

What are the key skills and qualifications needed to thrive as an informatics software engineer?

To thrive as an Informatics Software Engineer, you need expertise in software development, data analysis, and a strong understanding of informatics principles, often supported by a degree in computer science, bioinformatics, or a related field. Proficiency in programming languages (such as Python, Java, or R), database systems, and familiarity with healthcare data standards and tools like HL7 or FHIR are typically required. Strong problem-solving ability, collaboration, and effective communication are essential soft skills in this role. These skills ensure the development of robust, interoperable software solutions that support complex data-driven decision-making in healthcare and research environments.

How do informatics software engineers typically collaborate with clinical and research teams?

Informatics Software Engineers often work closely with clinicians, researchers, and data analysts to understand their workflow needs and translate them into robust software solutions. Collaboration involves frequent meetings to clarify requirements, iterative feedback on prototypes, and joint problem-solving to ensure tools meet regulatory and usability standards. This cross-disciplinary teamwork is essential for creating impactful applications that facilitate data integration, analysis, and reporting in healthcare or research settings.

What is the difference between Informatics Software Engineer vs Data Scientist?

AspectInformatics Software EngineerData Scientist
Required CredentialsBachelor's or Master's in Computer Science, Informatics, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentDevelops healthcare or research software, collaborates with clinicians or researchersAnalyzes data, builds models, and interprets complex datasets
Employer & IndustryHospitals, research institutions, healthcare tech companiesTech firms, finance, healthcare, research organizations

Informatics Software Engineers focus on developing software solutions tailored to healthcare and research environments, while Data Scientists analyze and interpret large datasets to inform decision-making. Both roles require strong programming skills and often overlap in data handling, but their primary goals differ: software development versus data analysis.

Can I be an informatics software engineer with an informatics degree?

Informatics software engineers typically have a background in computer science, software development, or related fields, and an informatics degree can provide relevant knowledge in data management and systems. However, gaining programming skills, experience with tools like SQL or Python, and understanding of healthcare or data systems are often essential. Additional certifications or practical experience can enhance job prospects in this role.

Is an informatics software engineer still in demand?

Informatics software engineers are in high demand due to the growing need for healthcare data management, electronic health records, and health IT systems. Skills in programming, data analysis, and familiarity with healthcare standards like HL7 or FHIR enhance job prospects in this field.

What are popular job titles related to Informatics Software Engineer jobs?

For Informatics Software Engineer jobs, the most frequently searched job titles are:

Infographic showing various Informatics Software Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 88% Full Time, 7% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.

Research Informatics Software Engineer

Manhattan, NY • On-site

Sci.bio Recruiting
Recruiting and Staffing Services • 11 - 50 employees
Learn more about Sci.bio Recruitingexternal

$226K/yr

Other

Posted 6 days ago

Job description

Research Informatics Software Engineer

Level : MS Level / Early Career


Location : New York City — primarily onsite with periodic remote flexibility.


About the Role

We’re looking for an MS-level Computer Science candidate to join a Research Informatics / R&D IT team at the intersection of scientific software, data engineering, cloud infrastructure, and AI.


This is an opportunity to help build the digital foundation supporting modern drug discovery — from cloud-native data platforms and laboratory informatics systems to data pipelines, LLM/RAG applications, and emerging agentic AI capabilities. The ideal candidate is technically strong, hands-on, and excited to apply modern software engineering and AI technologies to real-world scientific problems.


What You’ll Do

  • Build, integrate, and support LIMS, ELN, and analytical informatics platforms, working across data models, APIs, workflows, and scientific data flows.
  • Design scalable data pipelines and APIs that make scientific data FAIR, high-quality, and machine-actionable for researchers and AI systems.
  • Develop and support cloud-native infrastructure, primarily in AWS, using technologies such as Docker, Kubernetes, CI/CD, and workflow orchestration.
  • Prototype and productionize GenAI and agentic AI applications, including LLM agents, RAG/GraphRAG, retrieval pipelines, and multi-agent workflows.
  • Partner with scientists and engineering teams to translate research needs into reliable software, data products, and AI capabilities.
  • Apply strong software engineering practices around testing, schema design, performance, observability, and production deployment.
  • Help continuously improve the digital laboratory environment and its readiness to support increasingly AI-driven workflows.


What We’re Looking For

  • Master’s degree in Computer Science or a closely related technical field.
  • Strong programming skills in Python and SQL.
  • Experience building data pipelines, scientific workflows, or backend/data applications.
  • Hands-on experience with AWS, Docker/Kubernetes, PostgreSQL, and modern data engineering tools.
  • Exposure to AI/ML and LLM technologies, including RAG, retrieval, or multi-agent systems through coursework, projects, research, or professional experience.
  • Experience using modern AI coding assistants / coding agents such as Cursor, Claude Code, GitHub Copilot, or similar tools.
  • Strong interest in learning and working with scientific applications, laboratory data, and commercial informatics platforms.
  • Ability to work collaboratively across software engineering, data, and scientific teams.
  • Exposure to commercial LIMS/ELN or analytical platforms such as Genedata, CDD Vault, Virscidian Analytical Studio, or similar.


Nice to Have

  • Hands-on experience with LLM/agentic AI systems, RAG, GraphRAG, knowledge graphs, or multi-agent architectures.
  • Experience with PyTorch, Airflow, Prefect, or related ML/data tooling.
  • Experience with high-performance ML or scientific computing.
  • Familiarity with Neo4j or other knowledge-graph technologies.
  • Experience with production-grade software engineering, including CI/CD, testing, API development, schema design, and performance optimization.
  • Interest in applying modern AI and data engineering to laboratory workflows and drug discovery.


Apply