Job Description:

We are seeking a highly skilled and visionary Senior Solution Architect with deep expertise in Generative AI and AI/ML systems to lead the architecture and deployment of cutting-edge AI solutions. You will play a critical role in shaping and delivering intelligent products and platforms across the enterprise, helping drive innovation, scalability, and performance with responsible AI practices.

Key Responsibilities:

• Design and implement enterprise-grade architectures leveraging Gen AI (LLMs, RAG, embeddings) and ML pipelines.

• Lead solutioning efforts for AI-driven applications, including customer-facing products, internal copilots, and automation tools.

• Collaborate with cross-functional stakeholders – data scientists, engineers, product managers, and business leaders – to align architecture with use cases and business goals.

• Evaluate, select, and integrate Gen AI models (e.g., GPT-4, Claude, LLaMA, Gemini) and orchestration frameworks (LangChain, LlamaIndex).

• Architect scalable, cloud-native ML solutions using AWS, Azure, or GCP, integrating MLOps, LLMOps, and model governance best practices.

• Guide the development of retrieval-augmented generation (RAG), vector search, and fine-tuning pipelines for domain-specific applications.

• Ensure security, privacy, and ethical considerations are embedded in AI solutions from design through deployment.

• Provide technical leadership and mentorship across teams, driving innovation and ensuring architectural excellence.

Professional Skills:

• Databricks: Python, Spark, Delta Lake.

• Azure Cloud Services: Azure Data Factory, Azure Synapse, Azure Blob Storage

• Snowflake: Snowpipe, zero-copy cloning, RBAC (role-based access control)

• ETL Tools: Informatica, SSIS, Alteryx.

• 8+ years of experience in solution architecture, with 3+ years specifically in AI/ML systems and at least 1+ year in Gen AI.

• Proven experience designing and implementing end-to-end Gen AI solutions using LLMs, embeddings, vector databases, and orchestration tools.

• Deep knowledge of ML lifecycle and tools (e.g., MLflow, SageMaker, Vertex AI, Azure ML).

• Strong coding and prototyping skills in Python, with experience in Transformers, Hugging Face, OpenAI APIs, LangChain, etc.