Analyst - Data & AI

Overview

Analyst, Software Engineering role contributing to the design, development, testing, and support of data-driven and AI-enabled applications, working with senior engineers, architects, product teams, and business stakeholders in a regulated financial-services environment.

What you'll do

• Build next-generation AI engineering frameworks, chat agents, and automation capabilities that accelerate software delivery, along with global enterprise-scale data products using AI frameworks.
• Develop, test, and maintain Python-based application components, utilities, automation scripts, and data-processing services under the guidance of senior engineers.
• Write and optimize SQL queries for data extraction, validation, transformation, reconciliation, and application-support activities across relational databases.
• Design, consume, and support REST APIs, including request and response handling, authentication, input validation, error handling, logging, and integration testing.
• Contribute to AI-enabled application development using AWS Bedrock, including model invocation, prompt implementation, response processing, guardrails, and integration with enterprise applications.
• Assist in building retrieval-augmented generation (RAG), knowledge-base, document-processing, semantic-search, and chat-with-data capabilities using approved data sources and access controls.
• Use relevant AWS services such as Lambda, API Gateway, S3, RDS/Aurora, Step Functions, EventBridge, SQS, CloudWatch, IAM, Secrets Manager, KMS, and Bedrock to support cloud-native applications.
• Create unit and integration tests, participate in code reviews, troubleshoot defects, and follow secure coding, source-control, CI/CD, and software-development standards.
• Work with business analysts, product owners, developers, testers, and support teams to understand requirements and deliver reliable technical solutions.
• Create and maintain technical documentation, including API specifications, data mappings, implementation notes, support procedures, and knowledge articles.
• Provide production-support assistance by reviewing logs, analyzing application or data issues, documenting findings, and escalating complex problems to the appropriate teams.
• Follow applicable information-security, data-protection, responsible AI, change-management, and operational-risk requirements when handling banking data and AI-enabled functionality.

What you'll need

• Bachelor's degree (or foreign equivalent) in Computer Science, Information Technology, Information Systems, Software Engineering, Data Science, or a related field.
• Approximately 2-4 years of hands-on software-development, data-engineering, application-development, or related technology experience.
• Hands-on programming experience with Python, including functions, classes, exception handling, file and JSON processing, package usage, and automated testing.
• Working knowledge of SQL and relational databases, including joins, aggregations, subqueries, data validation, and basic performance considerations.
• Experience developing or integrating REST APIs and working with JSON-based request and response payloads.
• Practical knowledge of AWS cloud services and serverless application patterns; exposure to AWS Bedrock is required or strongly preferred.
• Understanding of Generative AI concepts such as prompts, tokens, embeddings, vector search, RAG, knowledge bases, model responses, and responsible AI safeguards.
• Familiarity with Git-based source control, code reviews, defect tracking, testing, and CI/CD concepts.
• Ability to analyze technical issues, communicate findings clearly, maintain documentation, and work collaboratively in a team environment.
• Good written and verbal communication skills, attention to detail, and willingness to learn new technologies.

Nice to have

• Experience in the financial services or banking industry is preferred.
• Experience using the AWS SDK for Python (Boto3) to integrate applications with AWS services.
• Exposure to AWS Bedrock model invocation, Knowledge Bases, Guardrails, Agents, or equivalent Generative AI capabilities.
• Experience with FastAPI, Flask, or a comparable Python API framework.
• Exposure to PostgreSQL, SQL Server, Oracle, or Amazon Aurora, including basic schema and query troubleshooting.
• Familiarity with vector databases or semantic-search technologies such as Amazon OpenSearch or PostgreSQL with pgvector.
• Understanding of document ingestion, chunking, metadata, embeddings, retrieval, source citations, and response validation.
• Familiarity with Amazon CloudWatch logging and monitoring, IAM permissions, KMS encryption, and Secrets Manager.
• Exposure to Terraform or another infrastructure-as-code tool, containerization, and automated deployment pipelines.
• Experience or interest in banking, credit risk, financial services, or other regulated business domains.

Details

• Location: MUFG Global Service Private Ltd., Bengaluru (BCIT).