Generative AI & LLMs : We are seeking a highly experienced and visionary Principal AI/ML Architect with deep expertise in Generative AI and Large Language Models (LLMs) to lead the design, development, and deployment of cutting-edge AI solutions. This role requires a strong blend of hands-on technical skills, architectural leadership, and a proven ability to drive innovation and build high-impact technical practices.

Key Responsibilities :

1. Generative AI Architecture Leadership: Lead the architectural design and implementation of scalable, high-performance Generative AI solutions and products utilizing LLMs.

2. RAG Pipeline & Retrieval Expertise: Architect and implement advanced Retrieval-Augmented Generation (RAG) pipelines, integrating sophisticated techniques for vector search, semantic retrieval, and indexing to enhance model context and accuracy.

3. LLM Integration & Orchestration: Drive the selection and integration of various state-of-the-art LLMs (e.g., OpenAI, Anthropic Claude, Google Gemini, Mistral) using specialized frameworks like LangChain, LlamaIndex, or PromptFlow.

4. Advanced Server Configuration (MCP): Apply deep technical expertise in configuring and optimizing MCP (Model Compute/Control Plane) servers, focusing on context routing, efficient memory management, and protocol-based interoperability to maximize model performance and throughput.

5. LLMOps & MLOps Strategy: Define and implement robust LLMOps/MLOps strategies, establishing continuous integration/continuous delivery (CI/CD) practices for AI models using tools such as MLflow, KubeFlow, LangSmith, and Weights & Biases (W&B).

6. Data & Orchestration: Provide architectural guidance on necessary data engineering pipelines and utilize orchestration tools (Apache Airflow, Prefect) to ensure reliable, high-quality data flow for model training and serving.

7. Technical Consulting & Client Engagement: Serve as a technical subject matter expert, engaging with clients and internal stakeholders to articulate the value, feasibility, and architecture of Generative AI solutions.

8. Practice Building: Drive the development of internal expertise and best practices in Generative AI, contributing to thought leadership and talent mentorship.

Education & Qualifications :

- Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field is highly preferred. Relevant certifications in cloud AI platforms (e.g., Azure AI Engineer, AWS ML Specialty, GCP Vertex AI) are a plus.

Required Skills & Experience:

- 12-15 years of overall experience with 5-7 years in AI/ML and 3+ years in Generative AI / LLM architecture.

- Strong hands-on experience with RAG pipelines, vector search, and semantic retrieval.

- Proven experience integrating LLMs (OpenAI, Claude, Gemini, Mistral, etc.) using frameworks such as LangChain, LlamaIndex, or PromptFlow.

- Deep understanding of MCP servers - configuration, context routing, memory management, and protocol-based interoperability.

- Strong programming skills in Python, and familiarity with containerization (Docker, Kubernetes) and cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex AI).

- Expertise in MLOps/LLMOps tools (MLflow, KubeFlow, LangSmith, Weights & Biases).

- Solid grounding in data engineering, pipelines, and orchestration tools (Airflow, Prefect).

- Excellent communication, client engagement, and technical presentation skills.

- Proven track record of practice building or leadership in emerging technology domains