Solution Architect
5 hours ago
About the Role:
We are seeking an accomplished Generative AI Architect to lead the design and implementation of cutting-edge AI-driven solutions. The ideal candidate will possess a strong background in Artificial Intelligence, Machine Learning, and Large Language Models (LLMs), with a proven ability to architect, prototype, and scale AI systems across enterprise environments.As a key technical leader, you will collaborate with product, data, and engineering teams to translate complex business challenges into innovative AI architectures using generative technologies such as OpenAI, Anthropic, Hugging Face, LangChain, and Vector Databases.
Key Responsibilities:
- Define and own the architecture strategy for Generative AI and LLM-based solutions across multiple business domains.
- Evaluate, select, and integrate AI frameworks, models, and platforms (e.g., OpenAI, Azure OpenAI, Vertex AI, Claude, Llama, etc.).
- Architect and deploy end-to-end AI pipelines, including data ingestion, model training, fine-tuning, and inference.
- Lead RAG (Retrieval-Augmented Generation), prompt engineering, and context management design for enterprise-grade solutions.
- Collaborate with data engineering teams to design scalable data architectures that support AI workloads.
- Drive POCs and pilot projects to assess model performance, latency, and cost efficiency.
- Ensure compliance with AI governance, ethics, and data privacy standards.
- Mentor and guide engineering teams in best practices for AI system design, MLOps, and deployment.
- Stay abreast of emerging trends in Generative AI, deep learning, and NLP to continuously enhance solution design.
Required Skills & Qualifications:
- Bachelors or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
- 12–15 years of total experience in software development, architecture, or AI engineering — with at least 3–5 years in AI/ML solution design.
- Proven expertise in Generative AI, NLP, and LLM-based architectures.
- Hands-on experience with transformer models (e.g., GPT, Llama, Claude, Mistral, etc.) and frameworks such as LangChain, LlamaIndex, Hugging Face Transformers.
- Strong proficiency in Python, with exposure to PyTorch, TensorFlow, or JAX.
- Experience integrating AI systems with cloud platforms — AWS Sagemaker, Azure AI, or Google Vertex AI.
- Familiarity with vector databases (Pinecone, FAISS, Chroma, Milvus) and embedding models.
- Understanding of microservices architecture, APIs, and containerization (Docker/Kubernetes).
- Excellent understanding of data engineering, model lifecycle management, and MLOps practices.
- Strong leadership, communication, and stakeholder management skills.
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