Agentic AI Architect
# Agentic AI Architect **Inizio Partners Corp** · United States · `Remote` · `Full Time` 💼 **Уровень роли:** `Senior` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Himalayas (JSON API)* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[Agentic-AI-Architecture]` `[AI-ML-Architecture]` `[Generative-AI-Engineering]` `[AI-Platform-Engineering]` `[Technical-Architecture]` `[Agentic-AI-Architect]` `[AI-Agent-Architect]` `[Agentic-AI-Solutions-Architect]` `[Agentic-AI-Engineer]` --- ### About the Role Role & Responsibilities Overview: Platform & Integration Design - Define integration architecture across - Lakehouse, ODS, document systems; Underwriting systems and third-party APIs - Design configurable, metadata-driven framework for multi-LOB onboarding - Define API/microservices patterns (Python/.NET hybrid) Technical Development, Execution - Perform hands on development and lead technical execution across AI, data, and platform teams - Guide engineers (AI, data, full-stack) and ensure alignment with architecture - Drive technical decisions and stakeholder communication Governance, Safety & ModelOps - Define AI safety and guardrails (PII, hallucination control, policy constraints) - Establish ModelOps and PromptOps frameworks - Ensure explainability, auditability, and traceability of AI outputs Architecture & Technical Leadership - Define end-to-end architecture for agentic AI-enabled platform across data, AI, orchestration, and integration layers - Design and govern agentic orchestration framework for multi-step workflows - Establish architecture patterns for - RAG and grounding, Vector search and retrieval, MCP tool access layer, prompt management and evaluation AI & GenAI Enablement - Define where and how to use - GenAI vs deterministic logic, agentic workflows vs pipeline workflows - Establish multimodal integration approach combining structured, unstructured, and external data - Design prompt lifecycle, evaluation, and optimization strategy Candidate Profile: - Experience : 10–15+ years in software/data/AI engineering with 4–6+ years in AI/ML/GenAI architecture - Background : Strong experience in designing enterprise-scale platforms and distributed systems - Domain (good to have) : Insurance / reinsurance / financial services - Education : Bachelor's or Master's in Computer Science, Engineering, Data Science, or related field - Profile Type : Hands-on architect with ability to balance strategy + execution Technical skills : - GenAI & Agentic Frameworks - Semantic Kernel/ LangGraph (or similar orchestration frameworks); LLM integration (Azure OpenAI, OpenAI APIs, etc.); Prompt engineering, prompt lifecycle design - Retrieval & RAG - Azure AI Search (indexing, vector search, hybrid search); Embedding pipelines and retrieval optimization; RAG design, grounding strategies, context management - Tool Access & Integration - MCP (Model Context Protocol) architecture and tool design; API design (FastAPI / REST / microservices); Integration with enterprise systems and third-party APIs - AI Safety & Governance - NVIDIA NeMo Guardrails;Microsoft Presidio (PII detection/masking); Guardrails for prompt injection, hallucination control - Evaluation & ModelOps - Azure AI Foundry (model hosting, versioning, monitoring); Evaluation frameworks (LLM-as-judge, test datasets); Prompt/version control, cost/latency monitoring - DevOps & Observability - CI/CD pipelines (Azure DevOps / GitHub Actions); Logging, monitoring, observability (App Insights, etc.); Performance tuning and scalability Originally posted on Himalayas
- Agentic-AI-Architecture
- AI-ML-Architecture
- Generative-AI-Engineering
- AI-Platform-Engineering
- Technical-Architecture
- Agentic-AI-Architect
- AI-Agent-Architect
- Agentic-AI-Solutions-Architect
- Agentic-AI-Engineer
Наблюдалась 2026-09-30, впервые 2026-09-29, источник — Himalayas (JSON API).