Job Summary
We are seeking a hands-on AI Architect to lead the design, development, enhancement, and deployment of an enterprise AI platform powered by Large Language Models (LLMs). The ideal candidate will combine strong software engineering skills with deep expertise in Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), and AWS cloud services to build scalable, secure, and production-ready AI applications. This role requires active involvement in solution architecture, software development, cloud deployment, performance optimization, and technical leadership.

Key Responsibilities
• Design, develop, and enhance an enterprise AI platform integrating multiple Large Language Models (LLMs).
• Architect and implement scalable AI solutions using Agentic AI frameworks and Retrieval-Augmented Generation (RAG) architectures.
• Build intelligent AI agents capable of reasoning, planning, tool execution, and workflow orchestration.
• Develop secure, scalable, and highly available cloud-native AI applications on AWS.
• Design and implement REST APIs and microservices to expose AI capabilities to enterprise applications.
• Integrate AI services with enterprise systems, databases, APIs, and third-party platforms.
• Deploy, monitor, and optimize AI workloads on AWS for performance, scalability, security, and cost efficiency.
• Work with product owners and engineering teams to translate business requirements into technical solutions.
• Drive architecture reviews, code quality, CI/CD automation, and engineering best practices.
• Evaluate emerging LLMs, AI frameworks, and cloud services to continuously improve the AI platform.
• Mentor developers and provide technical leadership across AI initiatives.

Required Qualifications
• Strong hands-on experience with foundation models such as OpenAI GPT, Anthropic Claude, Llama, Mistral, Amazon Nova, or similar models.
• Experience building enterprise-grade LLM applications.
• Strong expertise in Retrieval-Augmented Generation (RAG).
• Experience with prompt engineering, prompt optimization, embeddings, semantic search, and model evaluation.
• Experience integrating multiple LLM providers and implementing model orchestration.
• Hands-on experience with one or more Agentic AI frameworks, including LangChain, LangGraph, CrewAI, Microsoft Semantic Kernel, AutoGen, or Amazon Bedrock Agents.
• Experience developing multi-agent workflows, tool calling, function calling, memory management, and planning or reasoning agents.
• Strong hands-on experience with AWS services, including Amazon Bedrock, Amazon SageMaker, AWS Lambda, ECS/EKS, API Gateway, Step Functions, Amazon S3, DynamoDB, Amazon OpenSearch, Amazon Aurora, CloudWatch, IAM, VPC, EventBridge, and Secrets Manager.
• Strong proficiency in Python.
• Experience with FastAPI or Flask, REST APIs, microservices, Docker, Kubernetes, Git, and CI/CD pipelines.
• Experience with databases and search technologies such as PostgreSQL, DynamoDB, OpenSearch, Pinecone, Weaviate, Chroma, FAISS, or Milvus.
• Experience designing and deploying scalable, secure, and production-ready AI applications.
• Strong software engineering and solution architecture capabilities.

Preferred Qualifications
• Experience with Infrastructure as Code tools such as Terraform, AWS CDK, or CloudFormation.
• Experience building AI products from concept through production.
• Strong understanding of LLMOps, MLOps, observability, and AI monitoring.
• Experience implementing AI guardrails, responsible AI practices, and enterprise security controls.
• Familiarity with event-driven and serverless architectures.
• Knowledge of authentication, authorization, and API security.