Principal GenAI & Agentic AI Engineer

Role overview

Principal GenAI & Agentic AI Engineer at Sabre Corporation

Strategy & Architecture

This role also requires leading and developing data pipelines for necessary data layer for AI/ML.

Responsibilities

• Define reference architectures for GenAI apps, RAG systems, and agent ecosystems (single/multi-agent) on GCP using ADK.
• Leverage capabilities of Gemini Enterprise Agent Platform in the Agentic AI Product development.
• Establish domain and platform standards: model selection, RAG/generation patterns, memory architectures, security baselines, observability, and LLMOps .
• Lead portfolio-wide technical decisions (build/buy, vendor selection, SLAs, quotas) with a focus on reliability, safety, and cost control.
• Define the data pipeline development for lakehouse , delta lake or feature engineering.
• Solution Design & Delivery
• Architect and lead implementation of production-grade GenAI solutions (Vertex AI models, Grounding, Pipelines, Evaluation) and agentic services (planning, tools, memory, HIL).
• Design multi-tenant and hub-and-spoke patterns with Okta/IAP/Apigee for secure API exposure and tenant isolation.
• Drive end-to-end delivery across teams: data ingestion (Dataflow/Composer), indexing ( BigQuery vectors/Vertex Vector Search), services (Cloud Run/Workflows), events (Pub/Sub).
• Data Pipeline both near real time and batch.
• Platformization & Reuse
• Build and maintain prompt libraries, tool catalogs , agent templates, and evaluation harnesses for organization-wide reuse.
• Standardize LLMOps : CI/CD for prompts/models/agents, model registry, traceability, rollback, canaries, cost/performance scorecards.
• Enable a marketplace of agents/services with productized APIs, documentation, chargeback, and KPIs.
• Responsible AI, Security & Compliance
• Implement multi-layer guardrails: policy prompts, filters, memory governance, tool whitelisting, audit logs; ensure regulator-ready posture.
• Codify privacy, PII handling, data residency, and per-tenant isolation using VPC-SC, Secret Manager, IAM, and Apigee policies.
• Leadership & Enablement
• Mentor senior engineers and team leads ; run architecture reviews, design clinics, and red-team exercises.
• Drive continuous evaluation programs and publish org scorecards for quality, safety, and cost.
• Partner with Product, Security, and SRE to align roadmaps, SLOs, and operational playbooks.
• Required Technical Competencies
• Dataflow and Apache Beam for data pipeline development.
• Strong on using SQL for data analysis.
• LLM & GenAI: Model selection (Gemini & Model Garden), prompt engineering, RAG/grounding, multimodal pipelines, fine-tuning/adapter methods.
• Agentic AI (ADK): Agent loops, planners, tool/function design, memory (episodic/semantic/long-term), HIL, policy enforcement.
• Data & Retrieval: BigQuery (including vector functions), Vertex Vector Search, Document AI, Dataplex for lineage and governance.
• Orchestration & Services: Cloud Run, Workflows, Pub/Sub, Dataflow/Composer; HA/DR, backpressure, circuit breakers.
• LLMOps / MLOps : Vertex AI Pipelines, registry, CI/CD, trace correlation, cost/performance monitoring.
• Security & Compliance: IAM, Secret Manager, VPC-SC, private service connect, DLP, Okta/IAP, Apigee API policies.
• Observability & Cost: Central telemetry, user feedback loops, drift/outlier detection, quota/capacity planning.

Required qualifications

• 12–15+ years in software/data/ML engineering; 1 + years hands-on with LLMs/GenAI and agentic systems.
• Proven delivery of enterprise-scale GenAI/agent platforms on GCP (Vertex AI, BigQuery , Cloud Run, Pub/Sub, Workflows).
• Demonstrated impact in platformization , governance, and multi-team technical leadership.
• Strong proficiency in Java.
• Strong proficiency in Python/TypeScript (or equivalent) and infrastructure-as-code (Terraform/GCP Deployment Manager).
• Experience in security-by-design, privacy, and compliance audits.
• Proven delivery in building data pipeline using distributed computing frameworks such as Dataflow, Spark.
• 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.
• #LI-Hybrid#LI-GS1

Employment details

• Location: Bengaluru [Karnataka] [India]

Additional role details

• Powering the agentic revolution in travel.
• Sabre is an AI-native technology leader, backed by one of the world’s largest travel data clouds.
• Built on an open, modular, cloud-native architecture, Sabre serves as the backbone for both established leaders and bold, new disruptors, guiding them to the next age of travel retailing through intelligent, connected, and personalized experiences.
• With AI at its core and operating at unparalleled scale, Sabre transforms insights into innovation, empowering airlines, hoteliers, agencies and other partners to retail, distribute and fulfill travel worldwide.
• The Principal GenAI & Agentic AI Engineer is the technical leader responsible for designing, building, and scaling AI systems that combine LLM-powered GenAI and ADK-based agentic workflows on Google Cloud Platform.
• This role sets architecture standards, leads multi-team delivery, and governs safety, reliability, and cost at enterprise scale—accelerating product teams to achieve monetization of AI based products through reusable patterns, platforms, and guardrails.