AI Solutions Architect
Location: Onsite – San Francisco, CA Employment Type: Full-TimeAbout the Role:We are seeking an experienced AI Solutions Architect to lead the design, architecture, and delivery of an enterprise-scale Agentic AI platform. This individual will drive the technical vision for multi-agent AI systems, Retrieval-Augmented Generation (RAG), MCP-based tool integrations, and scalable microservices architecture that enables enterprises to compose, govern, and operate domain-specific AI agents at scale. The ideal candidate will have deep expertise in enterprise AI architecture, distributed systems, cloud-native engineering, and production-grade LLM platforms. This role requires both hands-on technical leadership and the ability to collaborate closely with engineering, product, presales, and enterprise stakeholders.Responsibilities:Lead the end-to-end architecture and implementation of multi-agent AI systems using frameworks such as LangChain, LangGraph, and Model Context Protocol (MCP)Design planner-executor patterns, sub-agent hierarchies, tool orchestration, retry logic, memory/context handling, and token optimization strategiesDevelop scalable agentic workflows supporting enterprise automation and reusable AI capabilitiesArchitect and optimize enterprise-grade RAG pipelines using vector databases such as pgvector and QdrantImplement hybrid retrieval, semantic search, re-ranking, and intelligent chunking strategiesGround AI agents using structured and unstructured enterprise knowledge sourcesDesign scalable reference architectures and AI solution blueprints for enterprise customersTranslate complex business requirements into scalable AI roadmaps and reusable platform acceleratorsSupport regulated and consumer-facing enterprise environmentsBuild event-driven microservices architectures leveraging Kafka, PostgreSQL, vector databases, and KubernetesDesign cloud-native deployment topologies optimized for high-throughput AI inference workloadsDevelop APIs and backend services using FastAPI, Node.js, Spring Boot, or similar frameworksEstablish AI engineering best practices across training, fine-tuning, prompt management, evaluation pipelines, drift detection, and rollback strategiesBuild structured evaluation frameworks and observability tooling for production AI systemsEnsure scalability, reliability, and governance across the Agentic Development Lifecycle (ADLC)Implement observability and monitoring solutions using Prometheus, Grafana, OpenTelemetry, and distributed tracing frameworksTrack agent reasoning, tool calls, token consumption, and quality metricsEnable auditability, compliance, and human-in-the-loop governanceCreate reusable AI engineering patterns, skills, sub-agents, evaluation harnesses, and platform componentsStandardize reusable development frameworks across multiple product and business linesDrive adoption of AI-assisted development tooling including Claude Code, Playwright MCP, Cursor, and related agentic engineering toolsSupport AI-enhanced planning, code generation, testing, and release validation workflowsPartner with sales, presales, and customer success teams on enterprise AI initiativesLead technical discovery sessions, workshops, architecture reviews, and AI roadmap discussionsSupport solution positioning and enterprise AI transformation initiativesQualifications:8+ years of software engineering and solution architecture experience3+ years of hands-on experience designing and deploying LLM-based or Agentic AI systems in production environmentsDeep expertise with, LangChain, LangGraph, Retrieval-Augmented Generation (RAG), MCP / AI tool orchestration, Prompt engineering, Context engineering, Token optimizationStrong programming experience in Python and TypeScript (Java preferred)Experience building scalable microservices using FastAPI, Spring Boot, Node.js, or related frameworksHands-on experience with, AWS, Azure, or GCP, Kubernetes, Docker, Terraform, CI/CD pipelinesStrong understanding of, MLOps, AI model lifecycle management, Evaluation framework, Drift detection, AI observabilityProven enterprise solution architecture experience translating business requirements into scalable AI solutions