AI Solutions Architect

7 hours ago

Nellore, Andhra Pradesh, India beBeeGenerative Full time ₹ 19,63,260 - ₹ 25,13,921
Job Title: AI Solutions ArchitectAs a skilled Ai Solutions Architect, you will be responsible for designing, developing and deploying AI/ML solutions with a focus on Generative AI and Large Language Models. Your expertise in fine-tuning and optimizing LLMs for domain-specific tasks using frameworks like LangChain, LlamaIndex or similar will be essential to drive business success.Key Responsibilities:
  • Design and develop AI/ML solutions focusing on Generative AI and Large Language Models (LLMs).
  • Fine-tune and optimize LLMs for domain-specific tasks using frameworks like LangChain, LlamaIndex or similar.
  • Integrate LLMs with APIs, databases, vector stores and enterprise applications.
  • Evaluate and implement model deployment strategies in various environments (on-prem, cloud, serverless or containerized).
  • Collaborate with cross-functional teams to deliver end-to-end AI solutions.
  • Stay updated with the latest advancements in AI, ML and GenAI research and propose adoption of new technologies.
  • Implement MLOps best practices for continuous training, deployment and monitoring of models in production.
  • Ensure responsible AI practices focusing on bias mitigation, data privacy and compliance.
Required Qualifications:
  • 5+ years of experience in software development preferably in Python, familiarity with Java, C# or Node.js a plus.
  • 2+ years of hands-on experience in Generative AI and LLM-based development.
  • Strong knowledge of AI/ML fundamentals including NLP, deep learning, embeddings and transformers.
  • Experience with LLMs such as OpenAI GPT, Anthropic Claude, LLaMA, Falcon, Mistral or similar.
  • Proven track record of delivering at least 2 production-grade LLM-based projects.
  • Experience with LangChain, LlamaIndex, Haystack or similar frameworks.
  • Familiarity with vector databases Pinecone, Weaviate, Milvus, FAISS, Chroma.
  • Hands-on experience with cloud platforms AWS, Azure, GCP and AI services Bedrock, VertexAI, Azure OpenAI.
  • Proficiency in containerization and deployment tools Docker, Kubernetes, CI/CD pipelines.
  • Experience with MLOps tools MLflow, Kubeflow, Weights & Biases for model lifecycle management.
  • Strong problem-solving, analytical and communication skills.

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