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IntegriChain

Life sciences data analytics for access

Automation & Process Improvement Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timePhiladelphia, PA, USANo salary listed

About the Job

Requirements

  • At least 4 years of experience automating and improving processes, or building integrations and software, ideally for a large or high-volume operation.
  • Demonstrated results automating real work, measured through time saved, errors reduced, or additional capacity.
  • Proficiency in Python or a similar language for scripting and building integrations.
  • Experience connecting systems through APIs and working with SQL and relational data.
  • Ability to identify process bottlenecks and redesign workflows before automating them.
  • Hands-on experience building working solutions with LLMs or agents, and using AI tools to accelerate work.
  • Working understanding of LLM patterns, including prompting, tool or function calling, and integrating agents into workflows.
  • Ability to work closely with non-engineering teams, translate their needs into solutions, and explain technical topics clearly.
  • Ability to work independently and adapt to shifting priorities in a fast-paced environment.
  • Troubleshooting and debugging skills, including for systems running in production.

Responsibilities

  • Work with an operations team to understand its workflows and identify high-impact automation opportunities.
  • Simplify processes before automating them by removing unnecessary steps and automating the remaining work.
  • Build scripts, scheduled jobs, API connections, and data pipelines to reduce manual work.
  • Connect internal tools, APIs, SQL databases, and other platforms so information can move without manual copying.
  • Measure processes before and after changes, track improvements, and continue refining them.
  • Monitor, maintain, and troubleshoot automations in production so they remain reliable.
  • Train team members to use new tools and workflows, and document them for adoption by other teams.
  • Design and build AI capabilities into delivered solutions, such as LLM-based reading and classification of unstructured text or agents performing multi-step tasks.
  • Use AI coding assistants such as Cursor, Claude, or Copilot while maintaining code quality.
  • Assess when AI is reliable and when deterministic automation is safer.
  • Write clean, maintainable code, primarily in Python, and follow version control, code review, and documentation practices.
  • Work with DevOps and Site Reliability Engineering on deployment, secrets, monitoring, and production health of automations.

Desired Qualifications

  • Experience with workflow automation, robotic process automation, or job orchestration tools.
  • Experience working with operations or managed services teams to roll out technology.
  • Hands-on experience with LLM APIs, tool or function calling, or agent-style workflows.
  • Experience deploying applications or services on AWS, including containers, serverless, secrets, identity and access management, or monitoring.
  • Experience with data platforms and analytics tools such as Snowflake, semantic models, or natural-language-to-SQL systems.
  • Experience with FastAPI, Streamlit, React, or similar frameworks.
  • Background in life sciences, healthcare, or pharmaceutical commercialization data such as master data management, patient data, or channel data.

About the Company

IntegriChain

Life sciences data analytics for access

IntegriChain provides data-driven analytics for the life sciences industry to improve patient access to therapies. It combines an subscription-based data platform with managed services to cover the full brand lifecycle, from pre-launch to post-market. Its platform collects and aggregates data and applies analytics to identify access obstacles and opportunities in areas like government pricing, rebates, and gross-to-net calculations, helping pharmaceutical manufacturers optimize distribution and pricing strategies. The company differentiates itself by offering an end-to-end solution that blends technology with hands-on managed services, serving a broad base of clients (more than 220 life sciences companies) and using private equity backing to expand capabilities. Its goal is to help clients remove access barriers and maximize patient access to therapies while improving commercial operations.

Company size
501-1,000
Company stage
Debt Financing
Total funding
$8M
Headquarters
Philadelphia, PA
Founded
2005

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