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AI Solutions Architect Agentic AI Platforms

SaaS Technologies

United States

United States

À propos

ROLE OVERVIEW We are hiring an AI Solutions Architect to lead the design and delivery of an enterprise Agentic AI platform. You will own the technical vision for multi-agent systems, RAG, MCP-based tool integration, and the underlying microservices that let enterprises compose, govern, and operate domain-specific agents at scale — and drive reusability by codifying patterns into shared skills and sub-agents across the Agentic Development Lifecycle (ADLC). KEY RESPONSIBILITIES • Agentic AI Architecture: Own end-to-end design of multi-agent systems using LangChain, LangGraph, and Model Context Protocol (MCP) — including planner-executor patterns, sub-agent hierarchies, tool routing, retries, and cost-aware token budgeting. • RAG & Knowledge Systems: Architect production-grade RAG pipelines with vector databases (pgvector, Qdrant), hybrid retrieval, re-ranking, and document-aware chunking to ground agents in enterprise knowledge. • Solution Architecture: Design reference architectures and solution blueprints for enterprise clients across regulated and consumer-facing industries — translating business outcomes into agentic AI roadmaps and reusable accelerators. • Scalable Microservices: Build event-driven microservices on Kafka, polyglot data layers with PostgreSQL and vector DBs, and Kubernetes-based deployment topologies for high-throughput inference workloads. • MLOps & Model Lifecycle: Establish practices spanning training, fine-tuning, prompt and config versioning, structured evaluations against golden datasets, drift detection, and automated rollback when output quality degrades. • Traceability & Observability: Instrument agent reasoning traces, tool-call audit trails, token spend, and quality signals with Prometheus, Grafana, and OpenTelemetry — enabling policy enforcement and humanin-the-loop oversight. • Reusable Engineering Standards: Codify AI engineering patterns (RAG retrievers, agent loops, eval harnesses, traceability spans) into reusable skills, sub-agents, and platform components consumed across multiple product lines. • Rapid Engineering in Agentic Development Lifecycle: Roll out AI-led developer tools and sub-agents (Claude Code, Playwright MCP) across planning, code generation, code review, test authoring, and release validation — accelerating delivery while standardizing quality. • Presales & Client Engagement: Partner with sales, presales, and customer success on enterprise pursuits — authoring solution designs, leading technical workshops, and shaping agentic AI roadmaps for prospects and existing clients. REQUIRED QUALIFICATIONS • 10+ years of software engineering experience, with at least 3 years architecting LLM-based or agentic AI systems in production. • Deep hands-on expertise with LangChain, LangGraph, RAG, MCP, prompt engineering, context engineering, and token optimization. • Strong programming skills in Python and TypeScript (Java a plus); proven ability to design and implement microservices with FastAPI, Spring Boot, or Node.js. • Production experience with cloud platforms (AWS, Azure, or GCP), Kubernetes, Docker, Terraform, and CI/CD pipelines. • Solid grounding in MLOps — model training/fine-tuning, evaluation pipelines, drift detection, and observability for AI systems. • Track record of solution architecture for enterprise clients — translating business problems into reference architectures and shipping production outcomes. • Bachelor's degree in Computer Science, Engineering, or a related field. NICE TO HAVE • Experience designing AI solutions for retail and e-commerce — personalization engines, conversational shopping assistants, product-catalog and price-intelligence agents, demand forecasting, and storeoperations automation. • Familiarity with retail data ecosystems (POS, OMS, PIM, loyalty, omnichannel inventory, customer-360) and grounding LLM agents on transactional and behavioral signals. • Awareness of retail trust and compliance concerns — PCI-DSS, GDPR / regional consumer-data laws, and brand-safety guardrails for customer-facing agents. • Experience in BFSI, payments, or other regulated industries (KYC/AML, audit & compliance, fraud and risk). • Familiarity with API gateways (Apigee, Kong), developer portals, Kong), developer portals, and exposure to Claude Code, Cursor, orsimilar agentic coding environments

United States

Compétences linguistiques

English

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