Senior DevOps Engineer / Hybrid / Boston, MA
This is a full-time hybrid opportunity with a rapidly growing Scientific Data & AI company building next generation cloud native platforms for large scale AI/ML workloads. You'll work with modern technologies across AWS, Databricks, and advanced MLOps tooling to help power AI driven scientific innovation. This role is ideal for someone who loves architecting scalable AI infrastructure and wants to influence a cutting-edge platform used by global scientific and data teams. You'll join a highly collaborative engineering culture where you can grow your cloud, ML, and LLM systems expertise while shaping the future of AI powered research. Required Skills & Experience
- 7+ years in software engineering or infrastructure engineering
- Strong AWS expertise and experience with IaC (CDK or CloudFormation)
- Production experience with AI/ML infrastructure and model lifecycle management
- Expert level Python and TypeScript
- Hands on experience with Databricks MLflow (model registry, versioning, serving)
- Strong understanding of Docker, CI/CD, and cloud native backend services
- Ability to design scalable, secure systems for real time and batch ML workloads
Desired Skills & Experience
- Familiarity with LLM orchestration frameworks (e.g., DSPy)
- Experience with LLM cost/latency optimization and usage analytics
- Knowledge of vector databases or embedding stores (e.g., OpenSearch)
- Experience integrating LLMs into production systems (RAG, semantic search)
What You Will Be Doing Tech Breakdown
- 70% AWS, Databricks, MLflow, IaC
- 30% Backend services (Python/TypeScript), containerization, CI/CD
Daily Responsibilities
- 80% Hands On Engineering
- 0% Management Duties
- 20% Team Collaboration
Specialization :
- Python
- DevOps
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