Senior Data Science Engineer

Job Summary

The Senior Engineer is hands-on technical expert responsible for designing and implementing data pipeline using dataflow and Beam, GenAI and Agentic AI solutions on Google Cloud Platform using Vertex AI and ADK frameworks. This role focuses on building production-grade systems, ensuring reliability, safety, and cost efficiency, and mentoring junior engineers while contributing to reusable patterns and best practices. The engineer should also develop data pipelines to load into lakehouse.

Key Responsibilities

Solution Design Development

• Implement GenAI workflows: prompt engineering, RAG pipelines, embeddings, and evaluation.
• Build agentic AI components: planners, tools, memory management, and guardrails using ADK.
• Integrate GCP services: Vertex AI, BigQuery (including vector functions), Cloud Storage, Pub/Sub, Cloud Run, Workflows.

Delivery Quality

• Write clean, maintainable code with proper documentation and testing.
• Ensure operational readiness: observability, logging, error handling, retries, and rollback mechanisms.
• Optimize performance and cost through caching, batching, and adaptive routing.

Collaboration Mentorship

• Work closely with Team Lead and Principal Engineer to align on architecture and standards.
• Mentor junior engineers on prompt engineering, agent design, and GCP best practices.
• Participate in code reviews, design discussions, and knowledge-sharing sessions.

Governance Compliance

• Implement security controls: IAM, VPC-SC, Secret Manager, and data residency requirements.
• Apply Responsible AI principles: safety prompts, content filters, and audit logging.

Required Technical Competencies

• 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.

Qualifications

• 5-8 years in software/data/ML engineering; 1-2 years in GenAI/agentic systems.
• Hands-on experience with GCP AI stack and ADK-based agent development.
• Strong coding skills in Python/TypeScript and familiarity with infrastructure-as-code.
• Hands-on experience on Java, Dataflow + Beam or Spark.
• Exposure to LLMOps practices and production deployments.

Outcomes KPIs

• 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.

Demonstrated Behaviors (Senior Engineer Level)

Technical Execution

• Delivers high-quality, tested code aligned with architecture standards.
• Proactively identifies performance and reliability improvements.

Collaboration

• Works effectively with team members; shares knowledge openly.
• Communicates risks and blockers early; seeks help when needed.

Responsible AI

• Applies safety and compliance measures consistently.
• Raises concerns about ethical or security risks promptly.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.