Model Developer, Assistant Vice President

Overview

Design, build, and deploy AI and machine learning models that turn complex data into production-ready solutions, partnering with business and technology teams to translate real-world problems into scalable applications and data pipelines.

What you'll do

• Design, build, and test scalable software applications using Python and SQL to support enterprise data and AI initiatives.
• Develop and integrate AI, generative AI, and machine learning models, including agentic frameworks and predictive capabilities, into production workflows.
• Architect and optimize complex SQL queries, stored procedures, and data models to extract and analyze large-scale datasets across distributed databases.
• Build reusable APIs, data ingestion pipelines, and automated services that streamline business processes and analytics.
• Automate data extraction, preprocessing, and feature engineering while identifying data quality issues and performance bottlenecks.
• Translate business requirements into technical specifications, architecture diagrams, and sprint deliverables in partnership with stakeholders.
• Lead solution demos, training sessions, and technical design walkthroughs for technical and non-technical audiences.
• Mentor team members through code reviews and design discussions while escalating technical risks and control gaps.

What you'll need

• 5+ years of professional experience in software development and data engineering.
• A bachelor's degree in computer science, software engineering, data science, information systems, or equivalent practical experience.
• Advanced Python skills, including object-oriented programming and frameworks such as FastAPI, Flask, Pandas, NumPy, PyTorch, TensorFlow, or LangChain.
• Advanced SQL, including writing and optimizing queries, indexing, and data models across relational and distributed databases.
• Building and operationalizing AI and generative AI models, including prompt workflows, embeddings, and large language model orchestration, in production settings.
• Software engineering practices such as Git version control, CI/CD pipelines, automated testing, Docker containerization, and agile methodologies.
• Communicating complex technical and AI concepts clearly to non-technical stakeholders and senior leadership while managing expectations across cross-functional teams.
• Analyzing and prioritizing dynamic requirements while managing multiple deliverables in a fast-paced environment.

Nice to have

• Building interactive dashboards and reporting solutions using Tableau or equivalent business intelligence tools.
• Working with distributed query engines such as Starburst, Trino, or Presto, and modern data lake architectures.
• Exploring Google Cloud Platform data services, Google Agent Development Kit, or other enterprise AI agent development platforms.
• Understanding of model validation, data lineage, role-based access control, and enterprise governance frameworks.

Details

• Location: Mumbai, Maharashtra, India.
• Work mode: hybrid, with 3 days in the office and 2 days working remotely each week.
• Employment type: full time.