Lead Software Engineer

Job highlights

• Build and optimize batch,real-time,and near-real-time integrations using IDMC or comparable integration technologies.
• Experience in the financial services or banking industry is preferred.
• Minimum Qualifications
• Experience with Amazon Bedrock knowledge bases or agents,Amazon SageMaker,Amazon OpenSearch,PostgreSQL / pgvector,LangChain,LlamaIndex,or comparable frameworks

Job Summary

Do you want your voice heard and your actions to count

Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world s leading financial groups. Across the globe, we re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.

With a vision to be the world s most trusted financial group, it s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career.

Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.

About the Role

Position Title : Lead Software Engineer

Corporate Title: AVP (Internal: AVP)

Reporting to : VP

Location: MGS - Bengaluru

Roles and Responsibilities

• Design, develop, enhance, and maintain complex ETL mappings, workflows, data pipelines, and UNIX/Linux shell scripts in enterprise data warehouse and data lake environments
• Build and optimize batch, real-time, and near-real-time integrations using IDMC or comparable integration technologies
• Develop advanced SQL and database solutions across SQL Server, Oracle, PostgreSQL, or comparable relational platforms, including performance tuning and data-quality controls
• Contribute to dimensional, canonical, and integration data models, and support data warehouses and data marts
• Build reusable Python, Java, or scripting components for data processing, orchestration, validation, automation, and operational support
• Design and build enterprise RAG solutions that retrieve trusted content and provide grounded responses using large language models
• Create and maintain knowledge ingestion pipelines covering document parsing, chunking, metadata enrichment, embedding generation, indexing, retrieval, and citation or source traceability
• Work with vector databases and semantic-search technologies such as Amazon OpenSearch, PostgreSQL with pgvector, or equivalent platforms
• Apply prompt engineering, hybrid search, reranking, context management, and retrieval evaluation techniques to improve answer relevance and reduce unsupported responses
• Build AI-enabled document intelligence solutions for extracting, classifying, summarizing, and validating information from structured and unstructured content
• Establish evaluation approaches for RAG and Generative AI solutions, including retrieval quality, answer groundedness, accuracy, latency, cost, and regression testing
• Implement responsible AI and model-risk controls, including data privacy, access control, content safety, human review, auditability, monitoring, and secure handling of confidential information
• Partner with architecture, security, data governance, model risk, legal/compliance, and business teams to move AI proofs of concept into supportable production services
• Design and support cloud-based data and AI solutions using relevant AWS services such as S3, RDS/Aurora, Redshift, Glue, Athena, Lambda, Step Functions, EventBridge, SQS, Kinesis, EMR, Textract, Bedrock, SageMaker, OpenSearch, IAM, KMS, CloudWatch, and Secrets Manager
• Design and deliver conversational chat with data solutions for banking use cases, enabling users to query governed structured and unstructured data through natural-language interfaces with appropriate access controls, source traceability, validation, and safeguards against unsupported responses
• Build resilient, observable, and cost-conscious architectures using infrastructure-as-code, CI/CD, automated testing, logging, metrics, and alerting
• Apply secure cloud engineering patterns for network connectivity, encryption, secrets, least-privilege access, service integration, and operational recovery
• Provide technical knowledge and understandings across design, development, testing, implementation, release, and production-support activit…