Custom Software Engineer

Project Role : Custom Software Engineer Project Role Description : Analyze, design, code and test multiple components of application code across one or more clients. Perform maintenance, enhancements and/or development work. Must have skills : Machine Learning (ML) Good to have skills : NA Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary: As a Custom Software Engineer, a typical day involves analyzing various client requirements and designing effective solutions tailored to those needs. The role includes coding and testing multiple components of application software, ensuring that each part functions seamlessly within the overall system. Additionally, the position requires ongoing maintenance and enhancement of existing applications to improve performance and address any issues. Collaboration with team members and stakeholders is a regular part of the day to ensure alignment with project goals and client expectations, fostering continuous improvement and innovation in software delivery. Roles & Responsibilities: - Expected to perform independently and become an SME. - Forward Deployed Senior AI/ML Engineer - What you'll do Lead the design, development, and production deployment of AI solutions across Machine Learning, GenAI, Agentic AI, and analytics use cases. - Build scalable ML and GenAI systems using Databricks, Snowflake, and modern cloud-native architectures. - Drive MLOps practices including CI/CD, monitoring, model governance, and operationalization. - Work closely with business stakeholders to translate complex problems into measurable AI solutions while mentoring junior data scientists and establishing engineering, documentation, and governance standards. - What we're looking for Strong hands-on experience in Python, SQL, PySpark, Databricks, APIs, and enterprise data platforms. - Proven expertise in ML, DL, NLP, GenAI/RAG, agentic systems, recommendation systems, forecasting, and experimentation. - Experience deploying ML/AI solutions into production with CI/CD, monitoring, MLflow, and MLOps best practices. - Exposure to MCP, multi-agent architectures, governance frameworks, and technical documentation (HLD, LLD, BRD). - Ability to independently lead solution design, interact with business stakeholders, and drive delivery of enterprise-scale AI initiatives. Professional & Technical Skills: - Must To Have Skills: Proficiency in Machine Learning (ML). - Experience with data preprocessing and feature engineering techniques relevant to machine learning projects. - Ability to implement and optimize machine learning models for various applications. - Familiarity with programming languages commonly used in machine learning such as Python or R. - Understanding of model evaluation metrics and validation techniques to ensure robust performance. - Knowledge of software development lifecycle and version control systems. Additional Information: