Ai Architect
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We are looking for a visionary and hands-on AI Architect to design, build, and deploy enterprise-grade AI production systems. In this role, you will bridge the gap between complex AI research and scalable, production-ready enterprise software.
Responsibilities
- Architect & Implement: Design and implement robust, scalable, and secure Generative AI solutions, including production-grade RAG architectures and multi-agent systems.
- Cloud Infrastructure Management: Architect AI workloads on cloud infrastructure, leveraging both AWS and Microsoft Azure services seamlessly.
- Data Strategy & Engineering: Design and optimize data architectures tailored for AI, integrating enterprise data platforms to feed LLM pipelines.
- Hands-on Development: Write production-quality Python code, build prototypes, and actively contribute to the core codebase alongside engineering teams.
- Model Deployment & Optimization: Select, fine-tune, optimize, and deploy open-source and proprietary Large Language Models (LLMs) effectively.
- Technical Leadership: Guide engineering teams on best practices for AI engineering, MLOps, LLMOps, and cloud infrastructure selection.
Qualifications
- Hands-on Python Expertise: Exceptional programming skills in Python, including deep familiarity with AI/ML libraries, asynchronous programming, and API development.
- Multi-Cloud Proficiency: Proven experience architecting and deploying AI solutions on both Microsoft Azure and AWS (e.G., AWS Bedrock, SageMaker, Azure OpenAI Service, Azure Machine Learning).
- Agentic Frameworks: Hands-on experience building autonomous workflows using advanced multi-agent orchestrators, specifically the OpenAI Agents SDK, Pydantic and similar.
- Enterprise Data Platforms: Deep technical expertise in integrating, querying, and managing data specifically within Databricks and Snowflake for AI training and inference context.
- Advanced RAG Architectures: Proven track record of designing and deploying sophisticated Retrieval-Augmented Generation systems, including experience with vector databases, advanced chunking strategies, hybrid search, and reranking mechanisms.
Nice-to-Have
- Conversational AI: Experience building, deploying, and optimizing enterprise chatbots and virtual assistants is a major plus.
- Open-Source LLM Deployment: Experience serving and optimizing open-source models (e.G., Llama, Mistral) using frameworks like vLLM, Hugging Face TGI, or Ollama.
- Experience with Temporal: Experience creating long running durable AI agents using Temporal will be a major plus
About Us
Grid Dynamics is a leading provider of technology consulting, agile co-creation, and scalable engineering services for Fortune 500 enterprises undergoing digital transformation. We combine business acumen with cutting-edge engineering to help enterprises deploy AI at scale, modernize core platforms, and implement next-generation cloud architectures.
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