Consulting-HC-IIO-HC Forward-AI Solution architect

Job description

# **Job Description – AI Solution Architect** The Human Capital Offering Portfolio focuses on helping organizations manage and sustain their performance through their most important asset: their people. Centered on five core issues, this Portfolio signifies to the market that we see Human Capital as a topic critical to the C-Suite. As we go-to-market, we will show our clients that we serve more than HR organizations – from the CEO to CFO, Risk Manager to Business Unit leader—and that we deliver on our issues and help create value for our clients. **Insights, Innovation & Operate Offering:** Our Insights, Innovation & Operate Offering is designed to enhance key aspects of our clients’ businesses by leveraging cutting-edge technology, data, and a blend of deep technical and human expertise. We innovate and deliver creative, industry-specific solutions that streamline operations and accelerate speed-to-value. **Position Summary:** AI Solutions Architect (Senior Consultants, Managers) ## **Role Summary** We are seeking an AI Solutions Architect to design and deliver production-grade AI agent platforms. The core of this role is building multi-agent orchestration systems using LangGraph and Anthropic Claude—routing user intent to specialized sub-agents, implementing retrieval-augmented generation (RAG) over policy documents, and performing actions. You will own the architecture from LLM prompt design to multi-tenancy and vendor integration across HR platforms (Workday, SAP, Oracle HCM). You will collaborate with engineering, security, and product teams to translate business requirements into production-ready AI agent solutions. **Experience bands:** - Senior Consultant: 6+ years total experience, with significant time in AI/ML solution design - Manager: 10+ years total experience, with significant time in AI/ML solution design ## **Key Responsibilities** - Design and implement multi-agent orchestration using LangGraph—intent classification, sub-agent routing, state management, checkpointing, and human-in-the-loop (HITL) interrupt flows. - Architect RAG pipelines: document ingestion, chunking strategies, embedding generation, vector search (pgvector), hybrid retrieval, and citation-grounded response synthesis. - Evaluate and integrate LLM providers (Anthropic Claude, OpenAI, etc.), defining model selection strategies, prompt engineering standards, and token budget management across agent tiers and multi-tenant data layers - Design vendor integration patterns using direct APIs, MCP, and A2A protocol for complex HR platform workflows. - Define end-to-end AI solution architectures from user interaction through agent orchestration, vendor API integration, and production deployment with monitoring. - , own the AI application architecture (agent orchestration, LLM integration, RAG, guardrails, eval frameworks) in joint partnership with the Cloud Solution Architect, who owns the cloud platform and infrastructure layer. - , partner with the Data Integration Architect who owns document ingestion and vector store architecture; own downstream AI application concerns (retrieval strategy, prompt design, response synthesis, evaluation). - Conduct architecture reviews and mentor teams on best practices in LLM application design, agent patterns, and production readiness. - Collaborate with stakeholders to translate requirements into architecture decisions and delivery roadmaps; produce HLD/LLD and ADRs. ## **Required Qualifications** - 6+ years (Senior Consultant) or 10+ years (Manager) total experience, with significant time in AI/ML solution design and implementation. - Hands-on proficiency with agent orchestration frameworks - LangGraph strongly preferred. - Strong understanding of retrieval-augmented generation - Experience with prompt engineering, tool calling, and LLM evaluation techniques - Expert-level Python development for production systems - Strong hands-on experience building API services with FastAPI - Working knowledge of multi-tenant security patterns - (Claude Code, GitHub Copilot, Cursor, Windsurf, or equivalent) for architecture work, design documentation, and engineering workflows. Familiarity with agentic engineering patterns is expected. - Strong communication and documentation skills; ability to influence cross-functional teams and senior stakeholders. ## **Preferred Qualifications** - Familiarity with the Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocol for vendor and cross-system integrations. - Experience integrating with HR/HCM platforms - Experience with LangFuse, LangSmith, or similar LLM observability and tracing platforms. - Knowledge of responsible AI practices: PII handling, prompt injection defense, model risk management, and explainability. - — working familiarity with cloud-native deployment (Kubernetes, CI/CD, IaC, observability), data engineering patterns (ETL/ELT, lakehouse, streaming), and the operational implications for AI platforms. Not expected to own these, but must collaborate effectively with Cloud Solution and Data Integration architects in joint reviews. ## **Key Competencies** - Architecture leadership with pragmatic trade-off decisions (speed vs. risk, cost vs. accuracy, build vs. buy, direct integration vs. protocol abstraction). - Ability to bridge AI research and engineering - turning prototypes into reliable, observable production services. - Strong ownership mindset for reliability, security, and operational excellence. - Coaching and standard-setting across teams. ## **Education** **Job Description – AI Solution Architect** The Human Capital Offering Portfolio focuses on helping organizations manage and sustain their performance through their most important asset: their people. Centered on five core issues, this Portfolio signifies to the market that we see Human Capital as a topic critical to the C-Suite. As we go-to-market, we will show our clients that we serve more than HR organizations – from the CEO to CFO, Risk Manag