Top Tech Jobs & Startup Jobs in Mumbai

Reviews and approves statistical modeling and analytics on large datasets to identify market trends, customer patterns, and business insights. Oversees data collection, quality, mining models, reporting, and analysis methodologies. Develops reports and recommendations for business, finance, and investment management, partners on strategic scenario modeling, and manages complex analytics projects with limited oversight.

Manages bank system administration, bank accounts, cash movements, payments, bank fees, banking relationships, and KYC compliance. Creates payment templates in the treasury system, manages treasury management system interfaces, tracks fees against budget, and supports regulatory, legal, and reporting compliance. The role requires financial analysis, forecasting, modeling, risk management, transaction processing, and treasury expertise.

Perform financial risk analysis, model development and validation for market risk. Collaborate with teams to build risk analytics systems.

Supports internal audits through data analytics, automation, continuous monitoring, and AI/ML model testing. Develops SQL and Python-based scripts, dashboards, exception reports, and automated testing routines; analyzes large datasets, validates findings, assesses controls and model performance, and communicates recommendations to audit and business stakeholders. The role also documents testing procedures, contributes to audit standards, resolves transactional issues, and partners with audit teams on complex engagements.

Designs and maintains secure, scalable AWS solutions for trading, risk, accounting, and reporting systems. Develops full-stack components, cloud architectures, ETL pipelines, APIs, Java microservices, and data integrations. Translates financial workflows into technical solutions, manages pricing and accounting feeds, and supports reconciliation, data accuracy, compliance, testing, monitoring, and documentation.

Designs and leads scalable AI platform infrastructure, agent frameworks, orchestration layers, backend services, APIs, and cloud deployments. Optimizes LLMs and fine-tunes small language models using techniques such as quantization, distillation, RAG, caching, and prompt optimization. Implements MCP integrations, supports enterprise multi-agent workflows, evaluates emerging AI tools, partners with stakeholders, mentors engineers, and establishes engineering standards.

Supports development and maintenance of core AI infrastructure, including AI agents, LLM and prompt optimization, backend services, APIs, cloud deployments, and MCP integrations. Writes tested Python code, troubleshoots infrastructure, participates in code reviews and sprint planning, and documents technical processes. Requires Python, AI agent, LLM, backend, AWS, and MCP knowledge, plus a bachelor's degree and at least three years of experience.

Leads hands-on development of scalable data engineering solutions using Python, Snowflake, Snowpark, and AWS. Designs serverless applications, stored procedures, and orchestrated DAG-based pipelines; optimizes performance and resolves production issues. Provides architectural guidance, establishes engineering standards, mentors engineers, collaborates with stakeholders, and contributes to platform modernization and technical roadmaps.

Develops and maintains business continuity, disaster recovery, crisis management, and contingency plans. Conducts business impact analyses, coordinates testing and emergency response, monitors compliance and readiness, reports exercise results, supports audits and regulators, and helps deliver continuity training and communications.

Leads Workday integrations and packaged application implementations, including customization, module implementation, enterprise application integration, and development using Workday Studio, EIB, Core Connector, and Workday Extend. Builds and deploys custom Workday applications, coordinates cross-functional product launches, establishes platform best practices, and supports adoption. Applies expertise in HR, payroll, and compensation while exploring AI, machine learning, and intelligent automation capabilities.