Top Tech Jobs & Startup Jobs in Mumbai

Perform credit due diligence and risk assessments, build and challenge financial models, produce credit memoranda with recommendations, manage portfolio exposures, recommend risk mitigants and structures, support transaction execution and system setup, partner with coverage/product teams and senior credit officers, monitor industry risks, and mentor junior staff.

Design, develop, and maintain production ML solutions for trade surveillance and financial crime. Perform end-to-end model lifecycle work (feature engineering, training, validation, calibration, monitoring), support model governance and audits, collaborate with SMEs and MLOps for CI/CD and productionization, deliver interpretable explainability outputs, and incorporate GenAI/LLMs for unstructured text signal extraction.

Design, develop, and maintain production ML solutions for trade surveillance and financial crime use cases. Apply supervised and unsupervised methods, execute model lifecycle (feature engineering, training, validation, monitoring), support model governance, partner with MLOps for CI/CD, deliver explainable outputs, and leverage GenAI/LLMs for unstructured data extraction and summarization.

Support India MLRO in AML transaction monitoring and investigations: review alerts from automated systems, assess suspicious activity, recommend escalation or closure, collaborate with regional teams, support regulatory exams, and contribute to AML policy/process updates. Focus on Corporate/Investment Banking AML typologies and ensuring quality and SLA adherence.

Design and deploy automated FP&A pipelines, validations, reconciliations, and dashboards using Python, SQL, and Databricks. Build finance-ready data models, implement data quality controls, support migration from legacy workflows, perform UAT and stakeholder training, and deliver governed self-service BI views to improve reporting efficiency and decision-making.

Lead enterprise data governance engineering programs across the firm. Manage roadmap and operating model for privacy-centric initiatives (consent, retention, cross-border transfer), oversee engineering delivery, KPIs, dashboards, and executive reporting. Drive adoption of cloud-native data platforms (AWS, Databricks, Snowflake), metadata/catalog/lineage, schema governance, and agentic AI-enabled engineering operating models while establishing governance, security, and reuse-first strategies.

Lead design and implement scalable Python backend solutions for derivatives migration on the Athena platform. Build OOP data models, persistence layers, APIs, and distributed/grid compute components; enforce CI/CD, automated testing, performance optimization, and secure AI-assisted engineering practices. Mentor engineers and collaborate with quants and traders to productionize pricing and risk workflows.

Lead or support data transformation and governance initiatives: define data strategies, collaborate with business and tech teams, improve data quality, enable analytics and visualization adoption, manage project timelines/resources, and develop documentation and training to promote data literacy.

Lead design and implementation of LLM-driven, multi-agent SDLC services and orchestration on AWS. Integrate agents with toolchains, build SDKs and data pipelines, drive AI-assisted engineering governance, mentor engineers, and ensure secure, validated AI workflows and observability.

Support CCR risk controls, monitor portfolio thresholds, perform ad hoc risk investigations, drive transformation and automation projects, develop analytical tools (Python/SQL/AI/LLM), and collaborate with Quants, Technology, Product and Credit Officers to strengthen exposure measurement, governance and reporting across derivatives and securities financing products.