AI- Technical Architect

Overview

We are seeking an experienced Technical Architect - AI Solutions with 8+ years of hands-on expertise in designing and delivering enterprise‑grade AI architectures. The ideal candidate will lead the development of scalable Large Language Model (LLM) integrations, Retrieval‑Augmented Generation (RAG) pipelines, and multi‑agent orchestration frameworks. This role is central to defining architectural standards, ensuring security and compliance, and driving innovation across our AI ecosystem.

Responsibilities

AI Architecture & Solution Design

• Architect and design end‑to‑end AI solutions, including LLM integrations, RAG pipelines, and multi-agent orchestration frameworks across enterprise systems.
• Build scalable, secure, and modular architectures for model training, fine‑tuning, inference optimization, and deployment.
• Define architecture blueprints, reference models, and reusable components to accelerate solution delivery.
  
  
  

• Establish and enforce technical standards, development best practices, and architectural guidelines for AI systems.
• Conduct architectural reviews, risk assessments, and compliance checks for AI deployments.
• Ensure adherence to enterprise security, privacy, and governance frameworks.
  
  
  

• Evaluate new AI, LLM, and vector database technologies for enterprise adoption.
• Recommend tools, platforms, and architectural approaches aligned with long‑term AI strategy.
• Drive innovation by experimenting with cutting-edge AI concepts, multi-agent systems, and automation frameworks.
  
  
  

• Design scalable cloud-native AI infrastructures across AWS, Azure, or GCP.
• Implement robust systems for distributed training, autoscaling, monitoring, and cost optimization.
• Integrate MLOps, CI/CD pipelines, model registries, and observability frameworks.
  
  
  

• Partner with product, data, engineering, and business teams to convert requirements into robust technical solutions.
• Lead technical discussions, decision-making, and system design workshops.
• Provide technical leadership during development, testing, and deployment phases.
  
  
  

• Implement Enterprise‑grade security controls, including identity management, encryption, and data governance for AI workloads.
• Optimize model latency, retrieval performance, and infrastructure scalability.
• Ensure compliance with regulatory standards related to AI, data privacy, and cloud deployments.
  
  
  

• Create detailed architecture documents, solution designs, technical guidelines, and deployment playbooks.
• Communicate complex AI and system design concepts to both technical and non‑technical stakeholders.
• Provide mentorship to engineering teams on AI architecture and best practices.
  
  
  

• Proven track record in enterprise AI architecture and solution design.
• Extensive experience building, deploying, and scaling production-grade AI systems.
  
  
  

• Expert-level knowledge of LLM fine-tuning, parameter-efficient training, optimization, and inference acceleration.
• Strong experience designing scalable RAG systems, embeddings pipelines, and retrieval optimization.
• Hands-on experience with vector databases such as Pinecone, Weaviate, FAISS, Milvus, or equivalent.
  
  
  

• Proficient in architecting AI systems on AWS, Azure, or GCP, with a focus on scalability and resilience.
• Strong understanding of containerization, Kubernetes, serverless architectures, and MLOps pipelines.
  
  
  

• Proficiency in microservices architecture, API gateways, and distributed system design.
• Strong understanding of integration patterns, messaging systems, and event-driven architectures.
  
  
  

• Expert understanding of enterprise security frameworks, IAM, encryption, and compliance requirements (data privacy, audit standards, etc.).
• Experience applying secure coding principles, threat modeling, and security-by-design in AI implementations.
  
  
  

• Exceptional technical documentation, architectural storytelling, and stakeholder communication skills.
• Ability to influence engineering decisions, mentor teams, and drive architectural direction.