DevOps Engineer
Listed on 2025-12-25
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IT/Tech
AI Engineer, Cloud Computing
Consultant Specialists, Inc. (CSI) provided pay range
This range is provided by Consultant Specialists, Inc. (CSI). Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range$65.00/hr - $85.00/hr
This position is W2 only and is onsite three days a week.
Job Title:
Dev Ops/Infrastructure
The CDI&A team collaborates with a broad range of stakeholders involved in the clinical development process (e.g., Clinical Science, Clinical Operations, Medical Writing, Quality, Regulatory).
It develops industry-leading solutions for highly complex business problems. To manage the design and pilot of these software products, they apply a high degree of ingenuity and creativity while maintaining a finger on the pulses of the rapidly changing tech and healthcare landscapes.
The Software Engineer will primarily be responsible for designing, developing, and deploying software which interacts with cutting-edge generative AI models and applications in collaboration with AI scientists, full stack developers, and others.
Their work will directly impact our ability to create and deliver innovative solutions that leverage AI to solve complex problems and enhance user experiences.
The Opportunity- Innovate and develop software applications to support clinical development.
- Identify and integrate AI/LLM capabilities to enhance data processing.
- Deployment and Monitoring:
Develop and maintain robust deployment pipelines for AI-enhanced applications and monitor pipeline performance in production, implementing necessary improvements. - Code Quality and Documentation:
Write clean, maintainable, and well-documented code. Participate in code reviews and contribute to best practices. - Research and Innovation:
Stay up-to-date with the latest advancements in generative AI and machine learning. Evaluate new technologies and methodologies to continuously improve our solutions. - Collaborate with Cross-Functional Teams:
Work closely with data scientists, engineers, and product managers to integrate generative AI capabilities into our products and services.
- An experienced full stack developer capable of bringing your expertise to our existing and upcoming AI applications/projects as both a leader and individual contributor.
- Someone with a clear understanding of the current landscape of AI & AI-based applications, including potential benefits, limitations, and standard of practice.
- Someone with experience in the automation and speed up of the software.
- Someone who brings additional skills to the software development process like Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
- 2+ years experience with front-end frameworks (preferably Vue.js).
- 2+ years of developing and deploying AI/ML solutions or applications.
- Experience designing and developing RESTful APIs (e.g. Python FastAPI).
- Proficiency with containerized workflows and architectures (Podman, Docker).
- 3+ years of Dev Ops experience with cloud platforms, specifically AWS (EKS, RDS, EC2).
- Experience with caching and data store technologies like Redis.
- Experience with CI/CD pipelines and automation tools (Git Lab CI, Git Hub Actions).
- Proficiency in Infrastructure as Code tools (Terraform, Cloud Formation).
- Experience with monitoring and observability tools (Port Key, Prometheus, Grafana, ELK stack).
- Experience with cloud data warehousing/analytics platforms (e.g., Snowflake, Big Query, Redshift).
- Knowledge of system administration, particularly with Linux.
- Experience with security best practices and compliance frameworks.
- Strong incident management and root cause analysis skills.
- Familiar with Agile methodologies.
- Excellent analytical and problem-solving skills with a track record of tackling complex technical challenges.
- Strong interpersonal and communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
- Extensive experience with cloud platforms (e.g. AWS) and modern data platforms (e.g., Snowflake).
- Experience implementing chatbots, retrieval-augmented generation (RAG) systems, and integrating LLMs into applications (AI-assisted automation).
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