Senior Solution Architect

About the Opportunity :

We are looking for an accomplished Senior Solution Architect GenAI / AI / ML to lead the architecture, design, and deployment of enterprise-grade artificial intelligence and machine learning solutions.

The ideal candidate will possess deep expertise in Generative AI (LLMs, GPT, BERT), Natural Language Processing (NLP), and Deep Learning, combined with strong proficiency in cloud-native AI platforms, data engineering, and MLOps frameworks.

This is a senior strategic role that blends architectural leadership with hands-on technical innovation enabling the design of scalable AI systems that integrate data pipelines, governance frameworks, and cloud-native deployment models.

The architect will collaborate with CXOs, data science teams, and engineering leaders to translate business goals into intelligent, production-ready AI ecosystems.

What Youll Do :

- Architect and design large-scale AI/ML and GenAI solutions, leveraging modern LLM architectures (GPT, BERT, Llama, Claude, etc.) for enterprise use cases.

- Lead end-to-end solution development encompassing data ingestion, model training, fine-tuning, orchestration, and deployment.

- Define architecture blueprints integrating data lakes, Spark-based data pipelines, and scalable ML infrastructure on Azure, AWS, or GCP.

- Drive MLOps strategy, automating workflows for model versioning, CI/CD integration, retraining, and monitoring.

- Design NLP-driven pipelines for entity extraction, summarization, text generation, and conversational AI.

- Ensure architectural compliance with AI governance, security, and ethical AI frameworks, including model transparency and data lineage.

- Collaborate with data scientists and ML engineers to select optimal models, frameworks, and deployment strategies.

- Define best practices for prompt engineering, fine-tuning LLMs, and leveraging GenAI APIs for domain-specific solutions.

- Guide cross-functional teams on data quality, feature engineering, and performance optimization.

- Conduct architecture reviews, POCs, and technical deep-dives to validate AI/ML design decisions and scalability.

- Advise leadership on AI roadmap, emerging technologies, and strategic platform choices.

What You Bring :

years of experience in AI/ML solution architecture, data engineering, and advanced analytics.

- Proven experience in designing and implementing GenAI solutions using LLMs such as GPT, BERT, T5, or custom transformer models.

- Strong understanding of Deep Learning frameworks (TensorFlow, PyTorch, Hugging Face) and distributed training workflows.

- Expertise in MLOps, CI/CD pipelines, model registries, and automation tools such as MLflow, Kubeflow, or Vertex AI.

- Proficiency in Python, SQL, and experience with Spark, Databricks, or Ray for large-scale data processing.

- Deep understanding of cloud AI ecosystems across Azure Machine Learning, AWS Sagemaker, and GCP Vertex AI.

- Knowledge of data lake architectures, Delta Lake, and real-time streaming pipelines.

- Strong background in AI governance, compliance, and responsible AI implementation.

- Ability to lead architecture discussions, influence technical decisions, and align AI design with enterprise objectives.

- Excellent communication, presentation, and stakeholder management skills, with experience engaging executive leadership.

- Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related technical discipline.

Preferred Skills :

- Experience in multi-LLM orchestration, RAG (Retrieval-Augmented Generation), and vector database integrations (Pinecone, FAISS, Weaviate).

- Familiarity with prompt engineering and custom fine-tuning of transformer models for domain-specific needs.

- Exposure to AI observability, model drift detection, and bias mitigation frameworks.

- Certifications in cloud AI services (Azure AI Engineer, AWS Machine Learning Specialty, or GCP Professional ML Engineer)