GenAI Engineer
Apply NowCompany: Tata Consultancy Services
Location: Atlanta, GA 30349
Description:
Must Have Technical/Functional Skills
Roles & Responsibilities
#LI-RJ2
Salary Range - $90,000-$120,000 a year
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- Strong proficiency in Python and frameworks like LangChain, Hugging Face, AutoGen, OpenAI API, and PyTorch/TensorFlow.
- Expertise in Large Language Models (LLMs): Experience working with GPT, Llama, Gemini, and custom fine-tuned models.
- AI Agents & Multi-Agent Systems: Knowledge of AI agent frameworks (AG2, CrewAI, AutoGPT, Autogen, etc.) and their real-world applications.
- Vector Databases & RAG: Experience with Azure AI Search, Chroma, or Pinecone for efficient retrieval and memory-based AI.
- Cloud AI & Model Deployment: Proficiency with Azure, GCP AI services, and deploying AI models in production environments.
- MLOps & AI Workflow Automation: Experience with model monitoring, optimization, and real-time AI agent performance tuning.
- APIs & Microservices: Strong experience in building AI-powered APIs, event-driven architectures, and AI workflow automation.
- Problem-solving & Scalability: Ability to design efficient, scalable, and modular AI architectures for real-world business applications.
- 6+ years of hands-on experience in AI/ML engineering, software development, or AI agentarchitectures.
- Strong proficiency in Python and frameworks like LangChain, Hugging Face, AutoGen, OpenAI API, and PyTorch/TensorFlow.
- Expertise in Large Language Models (LLMs): Experience working with GPT, Llama, Gemini, and custom fine-tuned models.
- AI Agents & Multi-Agent Systems: Knowledge of AI agent frameworks (AG2, CrewAI, AutoGPT, Autogen, etc.) and their real-world applications.
- Vecto r Databases & RAG: Experience with Azure AI Search, Chroma, or Pinecone for efficient retrieval and memory-based AI.
- Cloud AI & Model Deployment: Proficiency with Azure, GCP AI services, and deploying AI models in production environments.
- MLOps & AI Workflow Automation: Experience with model monitoring, optimization, and real-time AI agent performance tuning.
- APIs & Microservices: Strong experience in building AI-powered APIs, event-driven architectures, and AI workflow automation.
- Pr oblem-solving & Scalability: Ability to design efficient, scalable, and modular AI architectures for real-world business applications.
Roles & Responsibilities
- AI Agent Development: Design, build, and optimize autonomous AI agents and multi-agentarchitectures using frameworks like LangChain, AutoGen/AG2, CrewAI, RAG, and AI orchestrationtools.
- Generative AI Model Implementation: Work with LLMs (GPT, BERT, Llama, Gemini, etc.) to buildcustom AI solutions.
- AI Integration & Deployment: Implement AI-driven solutions using cloud AI platforms (AzureOpenAI, Google Vertex AI) and containerized environments (Docker, Kubernetes).
- Fine-tuning & Optimization: Customize and optimize LLMs, embeddings, and vector databases(Azure AI Search, Pinecone, Chroma) for retrieval-augmented generation (RAG).
- Enterprise AI Systems: Develop scalable AI-powered architectures that integrate with microservices,APIs, knowledge graphs, and automation workflows.
- MLOps & Continuous Deployment: Establish CI/CD pipelines for AI models, monitor AI agents inproduction, and ensure high performance and reliability.
- Cross-functional Collaboration: Work closely with AI researchers, software engineers, and businessteams to align AI solutions with enterprise needs.
- Responsible AI & Compliance: Ensure AI solutions comply with ethical AI standards, securitypolicies, and data privacy regulations.
#LI-RJ2
Salary Range - $90,000-$120,000 a year
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