Senior Data Science Engineer

Implement security controls: IAM, VPC-SC, Secret Manager, and data residency requirements.

Apply Responsible AI principles: safety prompts, content filters, and audit logging.

GenAI: Prompt engineering, RAG, embeddings, fine-tuning, evaluation metrics.

Agentic AI (ADK): Agent loops, tool integration, memory handling, planning strategies.

GCP Services: Vertex AI, BigQuery, Cloud Storage, Pub/Sub, Cloud Run, Workflows.

LLMOps: CI/CD pipelines, model registry, telemetry, cost/performance dashboards.

Security & Compliance: IAM, VPC-SC, DLP, Okta/IAP integration.

Data pipeline: Dataflow, Apache Beam, Java.

Delivery: Features shipped on time with minimal defects.

Quality: Evaluation metrics (faithfulness, grounding) meet thresholds.

Cost: Demonstrates cost optimization in design and implementation.

Team Contribution: Active participation in reviews, documentation, and mentoring.

Delivers high-quality, tested code aligned with architecture standards.

Proactively identifies performance and reliability improvements.

Works effectively with team members; shares knowledge openly.

Communicates risks and blockers early; seeks help when needed.

Applies safety and compliance measures consistently.

Raises concerns about ethical or security risks promptly.

We will give careful consideration to your application and review your details against the position criteria. You will receive separate notification as your application progresses.

Please note that only candidates who meet the minimum criteria for the role will proceed in the selection process.