Head of Engineering – GCP AI/ML, GenAI

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

👮‍♀️ Software Engineering Manager

👻 Ghost score 12%

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Naveera Technology LLC

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Naveera Technology LLC is a technology consulting and engineering firm that helps businesses become AI-first by building production-ready data engineering, machine learning, generative AI, application development, and IT infrastructure solutions. The company delivers end-to-end services—from data pipelines and cloud infrastructure to GenAI model development, MLOps, and custom web/mobile enterprise applications—focused on turning raw data into actionable intelligence and scalable systems. Naveera serves industries such as digital health, fintech, e-commerce, and enterprise clients through global delivery, extended teams, and a center-of-excellence model.

📋 Description

• Lead large-scale AWS-to-GCP data platform migration strategy and execution • Design and implement enterprise GCP data platforms, Data Lake and Lakehouse architectures, and Bronze, Silver, and Gold/Atomic data layers • Design and implement AI/ML and Generative AI solutions on GCP using Vertex AI and related GCP-native services • Build production-grade machine learning pipelines for preparation, training, validation, evaluation, deployment, monitoring, retraining, and lifecycle management • Develop GenAI and RAG solutions including enterprise search, document intelligence, AI assistants, summarization, semantic search, embeddings, vector search, and knowledge-management applications • Implement MLOps practices, model versioning, experiment tracking, validation, automated testing, deployment approvals, rollback, and environment promotion • Establish monitoring for model performance, data drift, latency, reliability, inference cost, response quality, retrieval accuracy, hallucination, and prompt injection risks • Ensure responsible AI, data privacy, security, governance, access control, auditability, and human-review processes • Analyze AWS platforms and map S3, Glue, Redshift, Athena, Step Functions, DMS, and Lake Formation workloads to GCP services • Architect real-time pipelines using Pub/Sub, Dataflow/Apache Beam, BigQuery, and Cloud Storage • Design and implement batch and streaming ETL/ELT, CDC, transformation, orchestration, and data processing pipelines using Python, PySpark, SQL, dbt, BigQuery, Cloud Composer/Airflow, and Dataflow • Define migration phases, technical dependencies, risks, rollback strategies, target-state architecture, and modernization opportunities • Design enterprise data models, dimensional/normalized/denormalized structures, multi-tenant data models, BigQuery partitioning and clustering strategies • Establish data governance, data quality, lineage, metadata, ownership, IAM, encryption, service accounts, network security, and data access policies • Lead Terraform-based infrastructure automation, CI/CD, testing, deployment, and provisioning across Dev, QA, UAT, and Production • Optimize BigQuery, Dataflow, Spark, Cloud Storage, streaming workloads, performance, SLAs, and cloud costs • Lead and mentor Data Engineers, Senior Data Engineers, and Technical Leads; provide technical direction, conduct architecture and code reviews, and define roadmaps • Act as primary technical contact for US-based stakeholders and collaborate with Business, Product, Data Science, BI, DevOps, Security, and Analytics teams • Translate business requirements into scalable technical solutions and communicate architecture decisions, risks, dependencies, timelines, trade-offs, and KPIs

🎯 Requirements

• 15+ years of experience in GCP Data Engineering, Data Architecture, Cloud Engineering, AI/ML Engineering, or related technology leadership roles • 5+ years of strong hands-on GCP Data Engineering experience • 3+ years of strong hands-on AI/ML & GenAI experience • Proven experience delivering AWS-to-GCP migration projects • Strong experience designing enterprise Data Lake and Lakehouse platforms on GCP • Strong hands-on experience with BigQuery, Google Cloud Storage, Dataflow, Pub/Sub, Cloud Composer, Dataproc, IAM, and Terraform • Experience migrating AWS data workloads, pipelines, and platforms to GCP • Strong knowledge of AWS and GCP service mapping, migration patterns, modernization strategies, and cloud architecture best practices • Experience designing, building, and deploying AI/ML solutions on GCP using Vertex AI • Hands-on experience with Generative AI, LLM-based applications, RAG architectures, embeddings, vector search, prompt engineering, and enterprise AI assistants • Strong understanding of MLOps, including model training, model registry, CI/CD/CT, model deployment, monitoring, retraining, governance, and rollback strategies • Experience implementing secure and responsible AI solutions, including data privacy, model evaluation, access controls, auditability, and governance • Expert-level SQL and strong Python and PySpark skills • Strong data modeling, data warehousing, batch processing, and real-time data engineering experience • Experience with Terraform, Git, GitHub, Cloud Build, CI/CD pipelines, and infrastructure automation • Experience managing and mentoring data engineering and cross-functional technical teams • Strong communication skills with experience working with US-based stakeholders • Google Cloud Professional Data Engineer certification preferred • Google Cloud Professional Machine Learning Engineer certification preferred • Experience with Vertex AI Agent Builder, Vertex AI Search, Gemini models on Vertex AI, or enterprise Generative AI platforms preferred • Experience with dbt, Apache Airflow, Kafka, Apache Spark, Kubernetes, Cloud Run, and API-driven architectures preferred • Experience with Dataplex, Data Catalog, data lineage, metadata management, data governance, master data management, and data-quality frameworks preferred • Experience supporting enterprise or regulated environments with strong data privacy, security, compliance, audit, and governance requirements preferred • Required technical skills include Python, PyTorch, TensorFlow, Scikit-learn, NLP, Deep Learning, ML Algorithms, GenAI, LLMs, GPT, Gemini, Claude, Llama, Prompt Engineering, Fine-tuning, RAG, Embeddings, Vector Databases, Semantic Search, Hybrid Search, Reranking, LangChain, LlamaIndex, LangGraph, Hugging Face, Transformers, AI Agents, Agentic Workflows, Tool/Function Calling, Multi-Agent Systems, MCP, MLflow, Kubeflow, Model Registry, Model Deployment, Monitoring, CI/CD, Vertex AI, Vertex AI Studio, Vertex AI Pipelines, Model Garden, Vector Search, FastAPI, Flask, REST APIs, SQL, Docker, Kubernetes, GCP, AWS, Azure, BigQuery, Dataflow, Spark, Databricks, Data Lakes, Advanced Python, Expert SQL, PySpark, Apache Spark, ETL, ELT, CDC, Batch & Streaming, Event-Driven Architecture, Data Pipeline Development & Optimization, Enterprise Data Lake/Lakehouse, Medallion Architecture, Data Warehousing, Data Modeling, Dimensional Modeling, Multi-Tenant Modeling, Schema-on-Read/Schema-on-Write, dbt, Apache Airflow/Cloud Composer, Dataproc, Dataflow/Apache Beam, AWS Glue, Redshift, EMR, Lambda, Kinesis, Athena, CloudWatch, GCS, AWS S3, Pub/Sub, Dataproc, Dataplex, Data Catalog, Terraform, Git/GitHub, Cloud Build, Infrastructure as Code, Data Lineage, Metadata Management, Data Quality, Monitoring, OpenLineage

🏖️ Benefits

• Flexible remote work • Exposure to global customers • Collaborative, innovation-driven culture • Continuous learning and certification • Lead transformative AI/ML & GCP innovations as Head of Engineering at Naveera Tech