Solutions Architects

We are seeking AI solution Architect more than 20+ year of experience and good experience in Coding side: JOB DESCRIPTION

AI Enterprise Architect

Key Responsibilities

AI Architecture & Strategy

Design and implement enterprise-grade AI architectures for investment platforms, trading systems, and financial analytics. Define and lead AI strategy aligned with investment performance, risk management, and regulatory requirements. Establish standards for Generative AI, Machine Learning, and real-time inference within financial systems. AI Solution Development:

Design, develop, and deploy AI models tailored to specific project requirements, including Cognitive AI techniques such as NLP, Computer Vision, Speech, and Conversational AI. Demonstrate strong understanding of Document AI development processes, models, and applications. Apply knowledge of Generative AI models and applications to relevant business use cases. Deliver and maintain production-grade, end-to-end machine learning solutions, including data preparation, experimentation, model training, serving, and updating. MLOps & Deployment:

Utilize MLOps methodologies to streamline development, deployment, and monitoring of machine learning models. Collaborate with data scientists, ML engineers, and stakeholders to transition prototypes to production environments. Optimize and refine algorithms to improve performance, scalability, and reliability. Integrate AI solutions into major cloud platforms (AWS, Azure, Google Cloud Platform). Implement CI/CD pipelines using Azure DevOps or TFS. Technical Leadership & Collaboration:

Provide technical leadership and mentorship to AI team members. Work closely with cross-functional teams to integrate AI solutions into products and services. Stay current with AI, LLMs, MLOps, and machine learning trends, techniques, and best practices. Requirements:

20+ years of experience in AI/ML, including practical experience with MLOps, Text Analytics, and Generative AI. Strong proficiency in Python and Java, with experience in frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn. Hands-on experience with cloud platforms (AWS, Azure, Google Cloud Platform). Expertise in machine learning and neural network architectures (Ensemble Models, SVM, CNN, RNN, Transformers). Experience with NLP tools (NLTK, SpaCy, Gensim) and MLOps tools (Kubeflow, MLflow, Azure ML). Practical knowledge of workflow orchestration tools (e.g., Airflow). Experience with Microservices architecture and building scalable REST APIs (FastAPI, Flask, Django). Proficiency with SQL and NoSQL databases (MongoDB, Postgres, Neo4j). Excellent problem-solving skills, collaborative mindset, and strong communication skills for diverse teams. Preferred Qualifications:

Bachelor s, Master s, or PhD in Statistics, Mathematics, Computer Science, or related quantitative field.