Software Engineer III

Fairygodboss; Hyderabad; On-site; INR 3,200,000 - 5,200,000; Full time

Job summary

JPMorganChase in Hyderabad is seeking a Software Engineer III to lead the design and delivery of scalable ML-enabled data products in a secure, scalable, and production-grade environment.

You will work on end-to-end pipelines, leverage enterprise AI tooling, and collaborate across teams to implement observability, security, and performance improvements in a fast-paced agile setting.

Qualifications

• 3+ years building and deploying ML systems in production.

Responsibilities

• Design, build, and maintain scalable ETL/data pipelines using Python and PySpark on AWS Glue and S3.
• Ensure data quality, reliability, and performance via validation checks, monitoring, and Spark/Glue optimization.
• Collaborate with upstream/downstream teams to gather requirements and deliver well-documented datasets/interfaces.
• Own end-to-end hands-on technical delivery, with Java exposure a plus.
• Leverages AI coding assist tools to improve code quality and productivity, with peer review and secure coding standards.
• Apply knowledge of SDLC tools, including AI-assisted development and automation for ML environments.

Skills

Python

PySpark

ML pipelines

APIs & testing

Tools

AWS Glue

S3

IAM

VPC

EC2

ECR

ECS/EKS

Lambda

CloudWatch

CloudFormation/Terraform

Spark

Athena

EMR

Job description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorganChase within the Consumer & Commercial Banking you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities

• Design, build, and maintain scalable ETL/data pipelines using Python and PySpark on AWS Glue and S3.
• Ensure data quality, reliability, and performance via validation checks, monitoring, and Spark/Glue job optimization.
• Collaborate with upstream/downstream teams to gather requirements, troubleshoot issues, and deliver well-documented datasets/interfaces.
• Own end-to-end hands-on technical delivery (100%), following engineering standards; Java exposure is a plus.
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• A reproducible training pipeline with automated validation and promotion to production.
• A low-latency inference service with monitoring, alerting, and drift detection.
• Infrastructure-as-code for ML environments with secure networking and least-privilege IAM

Required qualifications, skills, and capabilities

• 3+ years (or equivalent) building and deploying ML systems in production.
• Strong programming skills in Python and solid software engineering fundamentals (APIs, testing, design patterns).
• Strong hands-on experience with Python and PySpark for building production-grade ETL pipelines.
• Hands-on AWS experience, including several of: S3, IAM, VPC, EC2, ECR, ECS/EKS, Lambda, CloudWatch, CloudFormation/Terraform.
• Experience with data processing tools (e.g., Spark, AWS Glue, Athena, EMR) and SQL.
• Practical knowledge of deploying/serving models (REST/gRPC), performance tuning, and monitoring.
• Solid knowledge of ETL concepts, data modeling basics, and handling large-scale batch/incremental processing.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred qualifications

• Hands-on experience with AWS Glue (Jobs, Crawlers, Data Catalog) and Amazon S3.
• Strong SQL skills and experience implementing data quality / observability practices (reconciliations, validation checks, monitoring/alerting).
• Experience with CI/CD for data pipelines, Git-based workflows, and automated testing.