Senior AI Engineer
Tasks
- Architect and develop LLM agents
- Automate CI/CD with GitHub Actions
- Build RAG pipelines
- Deploy ML models with GPU scaling and autoscaling
- Design multi step agent workflow pipelines
- Embed security privacy and cost guardrails
- Enforce data governance and access controls
- Generate embeddings and persist to vector databases
- Implement blue green rollouts and cost telemetry
- Implement drift and quality monitoring with alerts
- Ingest data from BigQuery and object store lakes
- Instrument observability tracking metrics and structured logs
- Integrate LLM prompts external APIs and human in the loop escalations
- Mentor peers and set code standards
- Own ML lifecycle data preparation feature engineering fine tuning and evaluation
- Package and deploy services with Docker and Kubernetes
- Run A B or shadow tests
Perks/Benefits
- N/A
Skills/Tech-stack
Airbyte | Amazon Redshift | Avro | BigQuery | CI/CD | Docker | GitHub Actions | Grafana | Helm | Human-in-the-loop | Kafka | Kubernetes | Langchain | Llamaindex | LoRA | MLflow | N8n | PEFT | PGVector | Parquet | Prometheus | Python | Qdrant | RLHF | Ray | SQL | Spark | The Loop | Vector Databases
Education
Regions
Countries
States
Cities
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