Solutions Architect

As a Solution Architect specializing in Data, AI, and Generative AI with 8-10 years of experience, you will play a crucial role in designing and implementing complex technology solutions. Your deep technical expertise will be essential in translating business needs into scalable architectural designs. This strategic leadership position requires a combination of technical depth and cross-functional collaboration skills. Key Responsibilities: - Design and deliver end-to-end solution architectures utilizing cutting-edge technologies in data, AI, and generative AI. - Translate complex business requirements into technical blueprints and scalable architecture models. - Develop robust, high-performance frameworks while ensuring alignment with enterprise technology standards. - Lead and mentor engineering teams throughout the solution lifecycle, from design and prototyping to deployment. - Conduct architectural assessments, technology evaluations, and risk analysis to support strategic decision-making. - Drive rapid prototyping and proof-of-concept development to validate architectural concepts and business hypotheses. - Collaborate with business stakeholders, product managers, development teams, and C-level leadership to ensure technical alignment and delivery excellence. - Ensure compliance with security, performance, and regulatory standards. - Stay updated on emerging technologies and trends, particularly in LLMs, GenAI, and machine learning. Required Qualifications: - 8-10 years of experience in solution architecture focusing on data-driven and AI-centric systems. - Strong hands-on experience in designing solutions with large language models and generative AI technologies. - Successful track record in implementing enterprise-grade architectures across various business domains. - Solid full-stack development background with hands-on coding experience. - Expertise in at least one major cloud platform (AWS, Azure, or GCP). - Proficiency in programming languages such as Python, Java, or Scala. - Experience with data engineering tools and big data frameworks (e.g., Spark, Hadoop). - Advanced understanding of machine learning frameworks like TensorFlow, PyTorch. Technical Skills: - Cloud Architecture: AWS, Azure, GCP - Containerization & Orchestration: Docker, Kubernetes - Big Data Technologies: Spark, Hadoop - Machine Learning & GenAI: TensorFlow, PyTorch, OpenAI, Hugging Face, etc. - Data Pipeline & Workflow Design - API Development & Microservices Architecture Soft Skills: - Excellent communication and presentation skills for engaging both technical and non-technical audiences. - Strong leadership, mentorship, and stakeholder management abilities. - Strategic thinker with exceptional problem-solving and analytical skills. - Fast learner with an innovative, adaptive mindset for emerging technologies. - Proficient in rapidly conceptualizing solutions and transforming them into actionable plans.,