Associate Architect/Architect - Data & AI

As an experienced Architect, you will be responsible for driving data and AI streams, guiding projects from concept to production. Your role will involve designing, developing, and deploying robust, scalable, and real-world AI systems. **Key Responsibilities:** - Lead the architecture, design, and implementation of highly scalable and reliable data platforms and AI systems, including foundational data pipelines, data lakes, and real-time data streams. - Drive the end-to-end lifecycle of machine learning models, from experimentation and feature engineering to deployment, monitoring, and maintenance in a production environment (MLOps). - Mentor junior engineers, set best practices, and perform code reviews to ensure high-quality and efficient code. - Collaborate with clients technical and product teams to translate requirements into a clear technical vision and roadmap. - Stay updated with the latest advancements in AI, LLMs, machine learning, and data engineering to introduce new technologies and methodologies. - Partner with cross-functional teams to deliver integrated solutions. **Qualifications Required:** - 8+ years of hands-on experience in AI/ML and data engineering. - Proven experience in designing and implementing scalable AI systems in a production setting, with a deep understanding of MLOps principles and tools. - Proficiency with modern data platforms and tools such as Databricks, Snowflake, Apache Spark, Flink, Airflow, and Kafka. - Strong command of at least one major ML framework like TensorFlow or PyTorch, experience with LLMs and generative AI technologies is a plus. - Exposure to LLMs like Open AI, Claude, Gemini, and frameworks like LangChain, LangGraph, LangSmith, LangFlow. - Expert-level proficiency in at least one key programming language like Python, Scala, or Java. - Extensive experience with major cloud providers (AWS, GCP, or Azure) and their data and AI services. - Exposure to big data processing using PySpark or Databricks is advantageous but not mandatory. - Exceptional analytical and problem-solving skills, with the ability to tackle complex challenges independently. - Excellent communication and presentation skills to communicate technical concepts to technical and non-technical stakeholders. As an experienced Architect, you will be responsible for driving data and AI streams, guiding projects from concept to production. Your role will involve designing, developing, and deploying robust, scalable, and real-world AI systems. **Key Responsibilities:** - Lead the architecture, design, and implementation of highly scalable and reliable data platforms and AI systems, including foundational data pipelines, data lakes, and real-time data streams. - Drive the end-to-end lifecycle of machine learning models, from experimentation and feature engineering to deployment, monitoring, and maintenance in a production environment (MLOps). - Mentor junior engineers, set best practices, and perform code reviews to ensure high-quality and efficient code. - Collaborate with clients technical and product teams to translate requirements into a clear technical vision and roadmap. - Stay updated with the latest advancements in AI, LLMs, machine learning, and data engineering to introduce new technologies and methodologies. - Partner with cross-functional teams to deliver integrated solutions. **Qualifications Required:** - 8+ years of hands-on experience in AI/ML and data engineering. - Proven experience in designing and implementing scalable AI systems in a production setting, with a deep understanding of MLOps principles and tools. - Proficiency with modern data platforms and tools such as Databricks, Snowflake, Apache Spark, Flink, Airflow, and Kafka. - Strong command of at least one major ML framework like TensorFlow or PyTorch, experience with LLMs and generative AI technologies is a plus. - Exposure to LLMs like Open AI, Claude, Gemini, and frameworks like LangChain, LangGraph, LangSmith, LangFlow. - Expert-level proficiency in at least one key programming language like Python, Scala, or Java. - Extensive experience with major cloud providers (AWS, GCP, or Azure) and their data and AI services. - Exposure to big data processing using PySpark or Databricks is advantageous but not mandatory. - Exceptional analytical and problem-solving skills, with the ability to tackle complex challenges independently. - Excellent communication and presentation skills to communicate technical concepts to technical and non-technical stakeholders.