AI Engineer
Boston, MA, United States
USD 152K-214K (estimate) Senior-level Full Time
Tasks
- Automate infrastructure and deployments
- Build APIs and backend services
- Collaborate with product managers and data scientists in Agile sprints
- Create reusable connectors for multi model agents
- Deliver AI systems end to end
- Design ETL ELT pipelines to Databricks lakehouse
- Design and deploy multi model agents
- Develop agentic workflows with Python
- Enable low latency AI response with caching and vectorization
- Enforce security governance and access standards
- Implement LLMOps cost monitoring and latency optimization
- Implement rag pipelines
- Integrate front end using REST
- Monitor data quality and observability
- Orchestrate specialized multi agent workflows
- Translate product requirements into AI solutions
Perks/Benefits
- 401k match
- Backup daycare days
- Commuter benefits
- Dental insurance
- Life insurance
- Long-term disability
- Medical insurance
- Paid time off
- Short-term disability
- Virtual Care Options
- Vision insurance
Skills/Tech-stack
API Gateway | AWS Bedrock | AWS CDK | AWS KMS | AWS Lambda | AWS SDK | AWS SDK for Python | AWS SDK for Python Boto3 | AWS Step Functions | Airflow | Amazon API | Amazon API Gateway | Amazon CloudFront | Amazon ECS | Amazon EKS | Amazon S3 | CI/CD | Databricks | Databricks Workflows | Delta Lake | ELT | ETL | FastAPI | GitHub Actions | GraphQL | Infrastructure as Code | LLMOps | Langchain | Language Models | Large Language Models | Model versioning | Python | Python (Boto3) | RAG | REST | SQL | Step Functions | Terraform | Transfer Learning | Unity Catalog | Vector Databases | Vector Search | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
Cities
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