Our client, a leading pharmaceutical company, is hiring an LLM Application Engineer / Python Developer, on a contract basis.
Job ID #: 82217
Work Location:
Cambridge, MA and Lawrenceville, NJ – Hybrid role
Summary:
Seeking LLM Application Engineer to support our Life Sciences Research team. In this role, you will build modern cloud applications and solutions that facilitate drug discovery, generate predictive models for better therapeutic candidates, provide analytics and insights for scientific decision-making, and automate support activities around our applications and data processes. You will lead technical designs and processes to improve development practices, collaborate across teams to drive coordinated initiatives, and continuously learn and implement the latest technologies to drive advancements in our research outcomes.
Education/Experience:
- 7 years of engineering experience including 1 year of experimenting and building LLM augmented applications.
- Bachelors degree in Computer Science, Software Engineering, or related field; or equivalent work experience. A Masters degree is a plus.
- Experience with LLM Frameworks and APIs: Familiarity with LLM APIs and frameworks such as OpenAI API, Hugging Face, or other relevant platforms. Ability to integrate LLMs into applications using these APIs and frameworks.
- Full Stack App Development: Familiar with front-end, middle, and back-end development of web applications using python or react, api driven architecture, and database/warehouse management layer.
- Database Knowledge: Solid understanding of and experience implementing SQL and NoSQL database and data warehouse designs.
Knowledge/Skills:
- Programming Proficiency: Strong skills in Python (Streamlit), React, R (RShiny).
- Full Stack App Development: Familiar with front-end, middle, and back-end development of web applications using python or react, api driven architecture, and database/warehouse management layer.
- Database Knowledge: Solid understanding of and experience implementing SQL and NoSQL database and data warehouse designs.
- API Integration: Comfortable learning and interacting with commercial software APIs.
- Experience with LLM Frameworks and APIs: Familiarity with LLM APIs and frameworks such as OpenAI API, Hugging Face, or other relevant platforms. Ability to integrate LLMs into applications using these APIs and frameworks.
- Proven experience with AWS services and architecture.
- Familiarity with AWS CloudFormation and CI/CD DevOps processes.
- Understanding of cloud-native principles, microservices, serverless computing, and containerization.
- AWS Certifications including Associate, Solutions Architect, or DevOps Engineer – Professional.
- DevOps and Automation: Experience with CI/CD pipelines, version control (Git), and infrastructure-as-code tools. Ability to develop and implement automated testing frameworks.
- Security Best Practices: Knowledge of AWS security measures, including IAM, encryption, and network security.
- Adaptable to dynamic environments and changing priorities.
- Passionate about technology and healthcare, aiming to deliver excellent user experiences.
- Eager to learn new tools and continuously build innovative solutions.
- Proactive and collaborative team player with strong communication skills.
- Innovative thinker with strong problem-solving abilities.
- Demonstrated leadership and effective time management skills.
Responsibilities:
- Develop backend and full-stack applications using Python and React (experience with Streamlit & Rshiny is a big plus).
- Implement RESTful APIs and integrate with external software APIs (e.g., Spotfire, Genedata, Benchling).
- Collaborate with cross-functional teams to gather requirements and develop fit-for-purpose scientific applications.
- Design and optimize SQL and NoSQL databases/warehouses (Oracle, PostgreSQL, DynamoDB, Redshift).
- Utilize AWS services (e.g., ECS, Lambda, S3, RDS, DynamoDB, Aurora, Redshift) to build scalable and efficient applications and serverless computing.
- Deploy applications via robust CI/CD DevOps processes using tools like AWS CloudFormation, Git, AWS CodePipeline, CodeBuild, and CodeDeploy.
- Develop web applications that integrate Large Language Models (LLMs) APIs and frameworks and driving automated intelligence into application user experience.
- Utilize LLMs to automate data processing tasks, including data extraction, transformation, and loading (ETL).
- Implement Advanced text and data comprehension features by incorporating natural language processing capabilities such as text summarization, data analysis, and question answering into applications.
- Write high-quality, well-tested code with thorough unit, integration, and performance tests.
- Develop and integrate automated testing frameworks into CI/CD pipelines.
- Implement security measures, including identity and access management, encryption, and data lifecycle management processes.
- Monitor, troubleshoot, and optimize application performance. Lead automation strategies for system monitoring, testing, deployment, and scaling.
- Identify opportunities for process enhancements and implement innovative solutions.
Pay Range: $74-$76/hr