AI Lead/Architect

Overview

Hybrid
Depends on Experience
Full Time

Skills

LLM

Job Details

AI Lead/Architect

Location : Santa Clara, CA (Hybrid)

Full Time

Key Responsibilities

Design and oversee the architecture of AI-powered applications and platforms.

  • Collaborate with business and engineering teams to integrate AI Agents into production systems.
  • Define and enforce architectural standards, patterns, and best practices for AI systems.
  • Evaluate emerging AI technologies and recommend adoption strategies.
  • Lead modernization initiatives including cloud migration and microservices adoption.
  • Ensure scalability, performance, and security of AI-enabled solutions.
  • Provide technical leadership and mentorship to software engineers.
  • Partner with stakeholders to align AI architecture with business goals.
  • Architect scalable agentic AI frameworks using LangGraph, LangMem, and custom agent orchestration.
  • Design and implement advanced RAG architectures including hybrid search, query routing, and contextual retrieval.
  • Establish multi-agent systems with Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP).
  • Architect Small Language Model (SLM) integration for specialized tasks and cost optimization.
  • Establish comprehensive monitoring, observability, and performance optimization strategies.
  • Scope, manage, and drive complex GenAI projects and programs to successful completion.


Required Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or related field.

  • 5+ years of experience in software architecture and system design.
  • Minimum 4+ years of experience conceptualizing and architecting the target environment for AI solutions
  • Proven experience with AI technologies such as Azure OpenAI, Agentic Framework, AI Plugins, Content Understanding, DocIntelligence, Chunking Strategies, Indexing and Vectorization etc.
  • Strong knowledge of cloud platforms (Azure, AWS, Google Cloud Platform) and containerization (Docker, Kubernetes).
  • Expertise in .Net programming languages.
  • Familiarity MLOps practices

Preferred Skills

Experience with large language models (LLMs) and generative AI.

  • Knowledge of enterprise architecture frameworks.
  • Understanding of data privacy, ethics, and responsible AI principles.
  • Excellent communication and stakeholder management skills.
  • Certifications in AI technologies.
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