Falcon Smart IT (FalconSmartIT) · 7 hours ago
LLM Agentic AI Solution Architect
Santa Clara, CA
Full-time
Onsite
Senior Level, Lead/Staff
10+ years expFalcon Smart IT is seeking a Technical Architect specializing in LLMs and Agentic AI to lead the architecture, strategy, and delivery of enterprise-grade AI solutions. The role involves collaborating with cross-functional teams to design scalable solutions and ensure responsible deployment of Generative AI technologies across the organization.
Information Technology & Services
Hiring Manager
Harinii Suriyakumar
Responsibilities
Architect Scalable GenAI Solutions: Lead the design of enterprise architectures for LLM and multi-agent systems, ensuring scalability, resilience, and security across Azure and GCP platforms
Technology Strategy & Guidance: Provide strategic technical leadership to customers and internal teams, aligning GenAI projects with business outcomes
LLM & RAG Applications: Architect and guide development of LLM-powered applications, assistants, and RAG pipelines for structured and unstructured data
Agentic AI Frameworks: Define and implement agentic AI architectures leveraging frameworks like LangGraph, AutoGen, DSPy, and cloud-native orchestration tools
Integration & APIs: Oversee integration of OpenAI, Azure OpenAI, and GCP Vertex AI models into enterprise systems, including MuleSoft Apigee connectors
LLMOps & Governance: Establish LLMOps practices (CI/CD, monitoring, optimization, cost control) and enforce responsible AI guardrails (bias detection, prompt injection protection, hallucination reduction)
Enterprise Governance: Lead architecture reviews, governance boards, and technical design authority for all LLM initiatives
Collaboration: Partner with data scientists, engineers, and business teams to translate use cases into scalable, secure solutions
Documentation & Standards: Define and maintain best practices, playbooks, and technical documentation for enterprise adoption
Monitoring & Observability: Guide implementation of AgentOps dashboards for usage, adoption, ingestion health, and platform performance visibility
Innovation & Research: Stay ahead of advancements in OpenAI, Azure AI, and GCP Vertex AI, evaluating new features and approaches for enterprise adoption
Proof of Concepts: Lead or sponsor PoCs to validate feasibility, ROI, and technical fit for new AI capabilities
Ecosystem Expertise: Remain current on Azure AI services (Cognitive Search, AI Studio, Cognitive Services) and GCP AI stack (Vertex AI, BigQuery, Matching Engine)
Business Alignment: Collaborate with product and business leadership to prioritize high-value AI initiatives with measurable outcomes
Mentorship: Coach engineering teams on LLM solution design, performance tuning, and evaluation techniques
Qualification
Required
Minimum 12 years of experience
Bachelor's or Master's degree in Computer Science, Data Science, or a related field
10-12 years of experience in AI/ML-related roles, with a strong focus on LLM's & Agentic AI technology
Generative AI Solution Architecture (2–3 years): Proven experience in designing and architecting GenAI applications, including Retrieval-Augmented Generation (RAG), LLM orchestration (LangChain, LangGraph), and advanced prompt design strategies
Backend & Integration Expertise (5+ years): Strong background in architecting Python-based microservices, APIs, and orchestration layers that enable tool invocation, context management, and task decomposition across cloud-native environments (Azure Functions, GCP Cloud Functions, Kubernetes)
Enterprise LLM Architecture (2–3 years): Hands-on experience in architecting end-to-end LLM solutions using Azure OpenAI, Azure AI Studio, Hugging Face models, and GCP Vertex AI, ensuring scalability, security, and performance
RAG & Data Pipeline Design (2–3 years): Expertise in designing and optimizing RAG pipelines, including enterprise data ingestion, embedding generation, and vector search using Azure Cognitive Search, Pinecone, Weaviate, FAISS, or GCP Vertex AI Matching Engine
LLM Optimization & Adaptation (2–3 years): Experience in implementing fine-tuning and parameter-efficient tuning approaches (LoRA, QLoRA, PEFT) and integrating memory modules (long-term, short-term, episodic) to enhance agent intelligence
Multi-Agent Orchestration (2–3 years): Skilled in designing multi-agent frameworks and orchestration pipelines with LangChain, AutoGen, or DSPy, enabling goal-driven planning, task decomposition, and tool/API invocation
Performance Engineering (2–3 years): Experience in optimizing GCP Vertex AI models for latency, throughput, and scalability in enterprise-grade deployments
AI Application Integration (2–3 years): Proven ability to integrate OpenAI and third-party models into enterprise applications via APIs and custom connectors (MuleSoft, Apigee, Azure APIM)
Governance & Guardrails (1–2 years): Hands-on experience in implementing security, compliance, and governance frameworks for LLM-based applications, including content moderation, data protection, and responsible AI guardrails
Communication Skills: Communicate effectively with internal and customer stakeholders
Interpersonal Skills: Strong interpersonal skills to build and maintain productive relationships with team members & customer representatives
Problem-Solving and Analytical Thinking: Capability to troubleshoot and resolve issues efficiently
Analytical mindset
Ability to bring idea into reality through technology implementation & adoption
Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps
Provides regular updates, proactive and due diligent to carry out responsibilities
Preferred
Knowledge of MCP's and A2A SDK
Version Control: Proficiency with version control tools like Git
Agile Methodologies: Experience working in Agile development environments
Company
Falcon Smart IT (FalconSmartIT)
Global Specialist IT Recruitment Agency Leader in Digital Transformation , Business IT Solutions and IT Recruitment Specialists Falcon Smart IT is a Specialist recruitment agency can quickly find you highly skilled IT professionals who are the best fit for your project or full-time hiring needs.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase