Senior Agentic AI / LLM Platform Engineer

JOB DESCRIPTION

Senior Agentic AI / LLM Platform Engineer

Position Summary

Seeking a Senior Agentic AI / LLM Platform Engineer to architect and deliver a multi-agent AI system on Google Cloud Platform. The engagement covers four specialized AI agents-Model Builder, Solutions Canvas, Data Onboarding, and an Agentic Security Framework (AASO)-built on a shared TruAgent runtime with semantic, episodic, and procedural memory services. This is a hands-on technical lead role requiring deep expertise in LLM orchestration, agent frameworks, knowledge graphs, and production ML systems.

Key Responsibilities

• Architect the TruAgent shell runtime with multi-layer memory services (semantic, episodic, procedural) and knowledge graph integration
• Build Model Builder Agent: Data Scientist digital twin automating XGBoost, CGLM, Logit+WOE pipeline selection, feature engineering, and model validation
• Build Solutions Canvas Agent: Business intent-to-specification agent with UX flows and platform integration
• Build Data Onboarding Agent: Automated data profiling, GCDF/Metro-2 mapping, QC flows, and onboarding ticket generation
• Deliver Agentic Security Framework (AASO): Orchestrator with specialized Security, Compliance, Risk, Cloud Posture, and Incident Response agents integrated with SIEM/CSPM tooling
• Design and implement the semantic layer, knowledge graph persistence, and cross-agent knowledge sharing
• Integrate agents with enterprise platform APIs, CI/CD pipelines, and Google Cloud Platform AI/ML services (Vertex AI, BigQuery ML, Cloud Functions)
• Lead architecture decisions on LLM selection, prompt engineering, RAG pipelines, guardrails, and agent evaluation frameworks

Required Qualifications

• 7+ years software engineering with 3+ years focused on AI/ML systems; 2+ years hands-on with LLMs and agentic architectures
• Production experience building multi-agent systems using frameworks like LangChain, LangGraph, CrewAI, AutoGen, or custom orchestrators
• Deep Google Cloud Platform AI/ML experience: Vertex AI, BigQuery ML, Cloud Functions, Pub/Sub, GKE for model serving
• Strong knowledge graph and semantic layer experience (Neo4j, Apache Jena, or similar; vector databases like Pinecone, Weaviate, or Vertex AI Vector Search)
• Proven expertise in RAG architecture, prompt engineering, LLM fine-tuning, and evaluation/observability (LangSmith, Weights & Biases, or equivalent)
• Experience building ML pipelines: XGBoost, gradient boosting, logistic regression, feature stores, model registries
• Strong Python; familiarity with TypeScript/Node.js for full-stack agent UIs

Preferred

• Experience with enterprise data platforms, credit bureau data formats (GCDF, Metro-2), or financial services AI
• Background in AI security: adversarial testing, prompt injection defense, LLM guardrails, OWASP LLM Top 10
• Google Cloud Platform Professional ML Engineer or equivalent certification
• Experience with SIEM/CSPM integration for security agent orchestration

Core Technology Stack