Solution Architect

You will be responsible for architecting end-to-end AI/ML solutions tailored to business requirements, ensuring scalability and performance. Your experience in use case discovery, scoping, and delivering complex solution architecture designs to multiple audiences will be crucial, requiring an ability to context switch in levels of technical depth across AI/ML technologies and platforms. You will architect production level AI agent/RAG solutions for customers using the unified platform, including end-to-end ML pipelines, inference optimization, integration with cloud-native services, and MLOps. Providing guidance and best practices to development teams on AI agent implementations will also be part of your role. Your key responsibilities will include: - Overseeing the ingestion, transformation, and validation of large datasets for model training and deployment using AA or 3rd party hyper scaler platform. - Implementing and managing CI/CD pipelines for seamless model deployment and monitoring in production. - Tracking and improving the performance of AI/ML systems through testing, validation, and iterative improvements. - Staying updated on advancements in AI/ML and identifying opportunities for integrating new techniques into solutions. - Working closely with product managers, data scientists, and engineering teams to align on technical goals and deliverables. - Creating detailed architectural diagrams, technical documentation, and best practice guidelines. - Addressing critical production issues and optimizing system reliability and performance. - Mentoring team members and contributing to organizational learning in AI/ML technologies. Qualifications required for this role: - 7-10 yrs of overall IT experience with 5+ years of experience in AI/ML implementations. - Deep knowledge of machine learning, deep learning, and natural language processing algorithms and frameworks (TensorFlow, PyTorch, Hugging Face, etc.). - Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI. - Hands-on experience with AI/ML services on AWS, GCP, or Microsoft Azure. Have completed certifications from either of these hyper scaler providers. - Strong programming skills in Python, Java, or other relevant languages. - Familiarity with RAG (Retrieval-Augmented Generation) methodologies and integrating Generative AI into enterprise applications. - Hands-on expertise in prompt engineering, RAG, vector DBs, and technologies to implement AI agent solutions. - Expertise in data preprocessing, feature engineering, and working with large-scale data pipelines (Apache Spark, Kafka, etc.). Additionally, nice to have skills include: - Strong background on cloud services from various cloud service providers that integrate with AI/ML solutions. - Experience with MLOps tools like MLflow, Kubeflow, or SageMaker. - Proficiency in deploying, monitoring, and optimizing models in production environments. - Ability to design scalable, secure, and high-performance AI/ML solutions. - Strong analytical skills to address complex technical challenges and innovate scalable solutions. - Ability to articulate technical concepts to diverse audiences, including non-technical stakeholders. - Experience mentoring engineers and collaborating with cross-functional teams. - Understanding of data privacy and AI ethics for compliant system designs.,