Hybrid Role-GCP Lead-GenAI Remediation Platform , Dallas, TX
Nagaraju
GCP Lead – GenAI & Data Engineering
Job Title
GCP Lead – GenAI Remediation Platform
Location
Dallas, TX (Hybrid)
Job Summary
We are seeking a hands-on GCP Lead to drive the development and delivery of a scalable GenAI-powered remediation platform on Google Cloud Platform. The ideal candidate will lead engineering teams in designing modern data pipelines, implementing RAG-based AI workflows, and integrating enterprise legacy systems such as Mainframe (z/OS), AS400, and Splunk into a unified cloud-native ecosystem.
This role requires strong expertise in BigQuery, Vertex AI, Dataflow, Python/PySpark, and healthcare-compliant data governance practices.
Key Responsibilities
- Lead development and implementation of GenAI-powered remediation and incident management solutions on GCP.
- Build scalable ingestion pipelines to normalize data from Mainframe, AS400, Splunk, and enterprise systems into a Common Information Model (CIM).
- Design and optimize ELT/ETL pipelines using BigQuery, Dataflow, Pub/Sub, and PySpark.
- Implement RAG (Retrieval-Augmented Generation) workflows using BigQuery Vector Search and Vertex AI.
- Develop Human-in-the-Loop (HITL) workflows for low-confidence AI incidents and analyst feedback integration.
- Collaborate with data scientists and platform teams to improve model performance and retraining strategies.
- Implement healthcare-compliant governance controls including row-level security, masking, and secure AI inference.
- Automate deployments and infrastructure provisioning using Terraform and CI/CD pipelines.
- Mentor engineering teams and provide technical leadership across cloud, AI, and data initiatives.
- Communicate architecture decisions, AI trade-offs, and technical strategies to stakeholders and leadership.
Required Skills
- 10+ years of IT experience with strong expertise in GCP.
- Hands-on experience with:
- Vertex AI
- BigQuery
- Dataflow
- Pub/Sub
- Cloud Run
- Cloud Functions
- Strong knowledge of RAG architectures, embeddings, and vector search.
- Experience integrating Mainframe (z/OS), AS400, or other legacy enterprise systems.
- Strong Python, SQL, and PySpark development skills.
- Experience with Terraform and Infrastructure-as-Code.
- Familiarity with MLOps, model monitoring, and retraining workflows.
- Strong communication and stakeholder management skills.
Nagaraju
GCP Architect – GenAI & Enterprise AI Platforms
Job Title
GCP Architect – GenAI & Enterprise Data Platforms
Location
Dallas, TX (Hybrid)
Job Summary
We are looking for a highly experienced GCP Architect to design and architect enterprise-scale GenAI and RAG-based remediation platforms on Google Cloud. The ideal candidate will define end-to-end cloud architecture, establish BigQuery as the enterprise data foundation, and architect secure, scalable AI workflows integrating legacy systems, modern data platforms, and healthcare-compliant governance frameworks.
This role requires deep expertise in enterprise architecture, AI platform strategy, MLOps, and cloud-native modernization.
Key Responsibilities
- Architect end-to-end GenAI remediation platforms leveraging Vertex AI, BigQuery, and GCP-native services.
- Define enterprise data architecture and establish BigQuery as the centralized source of truth.
- Design scalable ingestion and normalization frameworks for Mainframe (z/OS), AS400, Splunk, and distributed enterprise systems.
- Architect RAG pipelines using embedding models, vector search, and BigQuery Vector Search capabilities.
- Design Human-in-the-Loop (HITL) frameworks integrating analyst feedback into AI model retraining pipelines.
- Define secure healthcare-compliant AI architectures with row-level security, data masking, encryption, and governance controls.
- Lead MLOps strategy including model lifecycle management, evaluation, observability, retraining triggers, and performance monitoring.
- Create reusable cloud architecture standards, deployment patterns, and Terraform-based automation frameworks.
- Provide architectural leadership across engineering, AI, infrastructure, security, and business teams.
- Present technical roadmaps, architecture decisions, and AI trade-offs to executive leadership and stakeholders.
Required Skills
- 12+ years of enterprise architecture and cloud engineering experience.
- Expert-level knowledge of GCP services including:
- Vertex AI
- BigQuery
- Dataflow
- Pub/Sub
- Cloud Run
- Cloud Functions
- Deep expertise in GenAI, RAG architectures, embeddings, vector databases, and LLM integration.
- Strong experience designing enterprise-scale data platforms and modernization programs.
- Experience integrating legacy Mainframe (z/OS), AS400, and enterprise operational systems into cloud ecosystems.
- Strong expertise in Python, SQL, PySpark, and Terraform.
- Experience implementing MLOps and AI governance frameworks.
- Strong leadership, communication, and stakeholder engagement capabilities.