Senior Agentic Platform Engineer

Senior Agentic Platform Engineer

location will be in Cupertino/Sunnyvale

Infosys / Apple

WebEx Hire

We are seeking a Senior Agentic Platform Engineer to serve as the lead architect and implementer for our Intelligence Layer. This role is designed for a senior individual contributor who can operate with high autonomy to design develop and deploy production-ready solutions that optimize both internal data operations and external-facing intelligence.

You will be responsible for the end-to-end delivery of the connective tissue between our multi-agent architecture and our knowledge graph supporting the existing team by accelerating technical milestones and hardening the CI/CD processes required for reliable AI deployment.

Core Delivery Categories

Agentic Systems & Orchestration: Lead the build-out of a multi-agent architecture using LangGraph. You will design cyclic stateful workflows implement persistence and manage Human-in-the-Loop (HITL) checkpoints.

Graph-Native Intelligence: Autonomously design the Ontology-to-Schema pipeline mapping OWL/SKOS enterprise ontologies into TigerGraph. You will develop high-performance GSQL and architect multigraph memory systems for agentic reasoning.

Trusted Data Materialization: Own the materialization of data products in Snowflake using dbt specifically focusing on the DQ rules engine and automated Trust Score computation.

Internal & External Skill Development: Design and deploy agents tailored for Internal Data Ops (automating metadata harvest and DQ remediation) as well as External-Facing Skills that provide governed high-trust insights to end-users.

Technical Expertise & Experience Requirements

• 10 years of Senior Software & Data Engineering experience with a proven track record of production delivery within a global enterprise environment.
• Advanced Agentic Orchestration (2 years): Deep hands-on mastery of LangGraph (StateGraph Command and Persistence) and LangChain.
• Multi-LLM Mastery: Expert implementation of frontier models (including Anthropic Claude OpenAI GPT and Llama) and the Model Context Protocol (MCP) for standardized tool-calling and context injection across model providers.
• TigerGraph & GSQL Specialist (5 years): Expert-level proficiency in GSQL development including writing distributed graph algorithms and optimizing complex sub-queries.
• Knowledge Modeling: Direct experience modeling enterprise ontologies using OWL SKOS or RDF and successfully mapping them to Labeled Property Graph (LPG) schemas.
• Analytics Engineering Mastery (5 years): Expert-level dbt (Core/Cloud) and Snowflake architecture with specific experience building automated Data Quality (DQ) monitors and trust-score pipelines.
• Development Stack: High proficiency in Python (specifically Asynchronous programming FastAPI and Pydantic) and advanced SQL.
• Internal Data Ops Optimization: Demonstrated experience building agents and skills specifically designed to automate Data Governance and Data Operations (e.g. automated glossary curation schema discovery and policy enforcement).

CI/CD DevOps & Process Optimization

Spec-Driven Development: Champion a Spec-First approach to AI development ensuring agent behaviors tool contracts and data schemas are defined via rigorous specifications (e.g. OpenAPI AsyncAPI or custom DSLs) before implementation.

AI-Optimized CI/CD: Support the team in designing and implementing robust CI/CD pipelines tailored for GenAI focusing on model-agnostic deployment patterns and high-frequency delivery cycles.

Process Engineering: Optimize team development workflows to support iterative AI loops including the implementation of specialized observability for agentic traces and automated feedback loops for data quality.

Preferred Experience

Unstructured Data & Vectors: Experience with unstructured data management and the implementation of vector databases (e.g. Pinecone Weaviate or Snowflake Cortex Search) within RAG architectures.

Enterprise Metadata Management: Hands-on experience with DataHub or similar data catalog and metadata management solutions to drive automated discovery.

Domain Expertise: Familiarity with Sales B2B and B2C data processes and associated tooling (e.g. Salesforce) including experience navigating CRM schemas for agentic tool-calling.

Governance & Security: Familiarity with data privacy and security frameworks (GDPR SOC2) as they apply to autonomous agents and Large Language Models.

Community Engagement: Contributions to open-source agentic frameworks or participation in the development of the Model Context Protocol (MCP) ecosystem.

Role Expectations for Contractors

Autonomous Execution: You are expected to take high-level architectural goals and drive them through to a deployed documented and production-tested state without daily supervision.

Team Support & Force Multiplication: Act as a technical anchor for the internal team removing blockers in the agent-graph interface and ensuring architectural consistency.

Stability & Observability: Your focus is on building resilient systems that are observable scalable and governed prioritizing long-term system health over simple prototyping.