Agentic AI Architect

Tiger Analytics is looking for experienced Agentic AI Architect with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

• 1. Architecture & Solution Design (50%)
  • Define the Blueprint: Design robust, secure, and scalable architectures for autonomous and semi-autonomous AI agents, multi-agent orchestration systems, and cognitive workflows.
  • Hyperscaler Implementation: Architect cloud-native AI pipelines leveraging specialized services across Azure (e.g., Azure OpenAI, AI Studio, Azure Functions),
    AWS (e.g., Bedrock, Sage Maker, AWS Lambda), or GCP (e.g., Vertex AI, Agent Builder, Cloud Run).
  • System Orchestration & Memory: Establish architectural patterns for LLM orchestration (Lang Chain, Lang Graph, Auto Gen, CrewAI), semantic memory storage (vector databases like Pinecone, Milvus, or cloud-native vector extensions), and state management.
  • Integration & Scalability: Ensure seamless integration of AI agents with legacy enterprise systems, APIs, RPA tools, and real-time data streams while optimizing for cost, latency, and throughput.
• 2. Hands-on Engineering & Prototyping (30%)
  • Rapid Prototyping: Actively write code to build Proof of Concepts (PoCs) and minimum viable products (MVPs) to validate architectural theories and de-risk complex agent workflows.
  • Code Quality & Governance: Establish production-grade coding standards for AI engineering. Conduct deep-dive code reviews to ensure reliability, security, and optimal prompt/agent behavior.
  • Framework Evaluation: Hands‑on evaluation of emerging AI frameworks, tooling, and foundational models (open‑source vs. proprietary) to determine enterprise viability.
• 3. Stakeholder Collaboration & Leadership (20%)
  • Translate Business to Tech: Partner with product managers and business stakeholders to translate vague business problems into structured agentic workflows and concrete technical requirements.
  • Technical Advocacy: Act as the subject matter expert on Agentic AI, educating internal engineering teams and advising executives on capabilities, limitations, and ROI.
  • AI Governance & Safety: Collaborate with Security, Compliance, and Risk teams to architect robust AI guardrails (e.g., NeMo Guardrails, Llama Guard), ensuring data privacy, hallucination mitigation, and ethical AI deployment.

• Technical
  
  Experience:
  
  
  • Cloud Expertise: 5+ years of experience architecting cloud solutions on at least one major hyperscaler (
    Azure
    , AWS
    , or GCP
    ), with a deep understanding of cloud‑native microservices and serverless paradigms.
  • AI/LLM Engineering: 2+ years of direct experience working with Large Language Models (LLMs) and building complex AI applications (RAG pipelines, autonomous agents, tool‑calling systems).
  • Agentic Frameworks: Hands‑on proficiency with orchestration frameworks such as Lang Graph, Semantic Kernel, Auto Gen, CrewAI, or Lang Chain
    .
  • Development
    
    Skills:
    
    Strong production‑grade programming skills in Python (preferred), Type Script, or Java, along with experience in CI/CD pipelines for AI (LLMOps).
  • Data & Search Infrastructure: Proven experience with vector databases and enterprise search engines (e.g., Azure AI Search, Amazon Open Search, Vertex AI Search).
• Leadership &
  
  Soft Skills:
  
  
  • Bilingual Communicator: Ability to explain complex machine learning or architectural concepts simply to non‑technical business leaders.
  • Pragmatic Mindset: Balanced approach between pioneering bleeding‑edge AI trends…