Generative AI Architect

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Company: Tata Consultancy Services

Location: Atlanta, GA 30349

Description:

Must Have Technical/Functional Skills
  • Hands-onexperience in designing and deploying AI-powered agents,multi-agent architectures, or autonomous systems.
  • Expertisein Large Language Models (LLMs) such as GPT, BERT, Llama, Gemini, and theirdeployment at scale.
  • Proficiencyin AI frameworks like AutoGen/AG2, TensorFlow, PyTorch, Hugging Face,LangChain, and RAG-based architectures.
  • Strongknowledge of retrieval-augmented generation (RAG), vector databases (Azure AISearch, Pinecone, FAISS, Chroma), and prompt engineering techniques.
  • Experiencewith cloud AI services (Azure OpenAI, Google Vertex AI) and containerizeddeployment using Docker, Kubernetes.
  • Strongbackground in API-driven development, microservices, and event-drivenarchitectures.
  • Experiencewith MLOps, CI/CD pipelines, monitoring AI models in production, andfine-tuning custom AI models.
  • Abilityto work with unstructured data, embeddings, and knowledge graphs for AI-driveninsights.
  • Excellentproblem-solving, analytical, and communication skills to work effectively withtechnical and non-technical teams.


Experience Required

  • Experience with AI orchestration/agents frameworks,including AG2, CrewAI, AutoGPT, and AgentOps.
  • Familiarity with Multi-modal AI models (text, image,video, audio) and AI personalization techniques. Knowledge of Responsible AIprinciples, including bias mitigation, explainability, and data privacyregulations.
  • Advanced academic background (PhD/Master's) in AI,ML, Data Science, or a related field


Roles & Responsibilities

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  • Define & Design AI Architectures: Establishscalable, modular, and efficient architectures for AI agents, LLM-basedapplications, and generative AI models.
  • Hands-on AI Development: Implement and optimizegenerative AI models, leveraging frameworks such as OpenAI, LangChain,LlamaIndex, AutoGen or AG2, RAG, and multi-agent systems.
  • AI Integration & Deployment: Work with cloud AIplatforms( Azure, GCP) and implement best practices for MLOps, model serving,and continuous improvement.
  • Enterprise AI Strategy: Align AI-driven solutionswith business objectives, ensuring scalability, security, andcost-effectiveness.
  • Cross-functional Collaboration: Engage with productteams, data scientists, and engineering teams to ensure seamless integration ofAI-powered solutions into business workflows.
  • AI Governance & Ethics: Establish responsible AIpractices, ensuring compliance with data privacy, model bias mitigation, andsecurity best practices.
  • Evaluation & Optimization: Continuously assessAI agent performance and optimize architectures for speed, efficiency, andcost-effectiveness


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SalaryRange - $100,000-$160,000 a year

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