Data & ML Ops Engineer

Role

Data/ML Ops Engineer

Location:

McLean, VA

Key Responsibilities:

• Prepare structured and unstructured data for RAG pipelines.
• Configure and manage vector databases and embeddings.
• Collaborate with AI engineer to integrate data into demo workflows.
• Ensure pipeline reliability, reproducibility, and observability.
• Support versioning, experimentation, and deployment infrastructure.

Requirements

• 3–5 years of experience in ML Ops, Data Engineering, or AI pipeline operations.
• Familiarity with LLM tuning, prompt engineering, or semantic search.
• Experience with cloud platforms (AWS/GCP/Azure).
• Understanding of security and privacy in AI data pipelines.
• Comfortable working on short-term, high-impact innovation sprints.
• Experience working in agile environments.

Experience With The Following Technologies:

• AWS Bedrock, Anthropic Claude models (Claude Sonnet 4.5, Claude Haiku 4.5, Claude Opus 4.5)
• PostgreSQL (RDS), AWS S3 (versioned, encrypted)
• AWS (ECS Fargate, Lambda, EventBridge), Terraform, Docker
• Prometheus, CloudWatch Logs/Metrics/Alarms, structured JSON logging
• AWS KMS, Secrets Manager, IAM role-based access
• Compliance: NIST 800-53, FedRAMP, SOC 2, PCI DSS