Sr Lead Software Engineer - Java Python Data Engineering

JPMorganChase; Hyderabad; On-site; INR 300,000 - 600,000; Full time

Job summary

JPMorgan Chase in Hyderabad seeks a Senior Lead Software Engineer to drive secure, scalable data-engineering platforms supporting KYC and risk assessment initiatives. You will lead architecture, set engineering standards, and mentor engineers across teams.

The role emphasizes production-grade code, agentic AI systems, and governance of LLM-based applications in regulated environments. Strong communication with senior leaders is essential.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands-on experience delivering system design and enterprise-scale development.
• Experience designing and deploying production AI/ML systems in regulated environments.

Responsibilities

• Develop secure, high-quality production code for data-intensive applications.
• Create durable software frameworks and patterns used across teams.
• Design and govern agentic AI systems with multi-agent workflows and tool-use integrations.
• Establish engineering standards for LLM-based applications ensuring safety and observability.
• Drive adoption of advanced methods aligned with product development.
• Advise cross-functional teams on technical matters in your domain of expertise.
• Apply SDLC tools to improve automation at scale.

Skills

Advanced programming

Python

Java

LLM-based applications

AI/ML systems

Data engineering

Cloud platforms

System design

Production code

Public speaking/communication

Job description

Job Description:

Join a team where your advanced engineering skills drive impactful solutions for a global financial leader. Grow your career while shaping the future of data-driven risk assessment.

Job summary

As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Sector Data Engineering team, you will deliver secure and scalable solutions that support the firm's Global Know Your Customer (KYC) and Risk Assessment Data Platform. You will collaborate with talented colleagues to drive best-in-class outcomes and set engineering standards. Your leadership will help define architecture and practices across multiple teams. Together, we create trusted platforms that power the firm's critical risk management initiatives.

Job responsibilities

• Develop secure, high-quality production code for data-intensive applications and platforms, and mentor other engineers
• Create durable, reusable software frameworks and patterns leveraged across teams and functions
• Design and govern agentic AI systems, including multi-agent workflows, tool-use integrations, and human-in-the-loop controls for regulated environments
• Establish engineering standards for LLM-based applications, ensuring safety, observability, and reproducibility at scale
• Drive adoption of advanced technical methods and practices aligned with industry standards and product development methodologies
• Advise cross-functional teams on technological matters within your domain of expertise
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including AI-assisted development and automation capabilities, to improve automation at scale

Required qualifications, capabilities and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale
• Hands-on experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures with tool use, memory, and multi-step reasoning in regulated environments
• Expert in one or more programming languages, particularly Python and/or Java
• Advanced knowledge of software application development and technical processes, with considerable depth in one or more disciplines (e.g., cloud, AI/ML, data engineering)
• Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)
• Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance
• Practical cloud-native experience (AWS, Azure, or GCP)
• Ability to present and effectively communicate with senior leaders and executives

Preferred qualifications, capabilities and skills

• Experience with modern data platforms such as Databricks or Snowflake
• Deep hands-on experience with Spark/PySpark and other big data processing technologies
• Expertise in open-source table formats and catalog services such as Apache Iceberg
• Experience with LLM orchestration frameworks and model serving infrastructure or managed endpoints (AWS Bedrock, Azure OpenAI)