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Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Manage enterprise customer accounts as a trusted technical advisor, driving platform adoption, measurable business value, and technical ROI. Develop success plans, troubleshoot complex hardware, software, and API issues, manage escalations, conduct root-cause analysis, and lead technical reviews. Collaborate with Sales, Support, Product, and Engineering while communicating effectively with technical and executive stakeholders. Use AI tools to improve customer insights and outcomes, and contribute to knowledge sharing and team development.
Top Skills:
AIAPIsGainsightGongInternet Of Things (Iot)JIRAPaasPythonSaaSSalesforceTableauZendesk
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Principal Data Engineer responsible for setting enterprise data-platform strategy and architecture across multiple teams. Defines standards for Databricks, Spark, dbt, DataOps, CI/CD, and observability; leads platform architecture, technology evaluations, migration, scalability, deployment, and cost strategy. Resolves complex cross-cutting data challenges, mentors senior engineers, influences architecture decisions, and partners with leadership on long-term roadmaps.
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Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Lead the strategy, architecture, and evolution of enterprise data platforms supporting secure data exchange, discovery, governance, integration, and self-service consumption. Establish scalable patterns for data quality, lineage, observability, privacy, and security while reducing bespoke workflows through automation. Provide technical leadership across engineering organizations, influence architecture decisions, mentor technical teams, and translate complex business needs into reusable cloud and on-premises data solutions.
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Develops and supports secure, scalable Java software within an agile Asset and Wealth Management technology team. Collaborates directly with investment professionals, deploys production updates, reviews and debugs code, and influences application design and technical operations. Uses CI/CD, SRE tooling, messaging technologies, testing frameworks, and AI-assisted development tools. Provides technical guidance, promotes engineering standards, and validates AI-generated code for quality, performance, security, and responsible use.
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 Asset and Wealth Management Technology team, 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
- Collaborates confidently directly with Investment Teams, Traders, and Portfolio Managers, effectively bridging communication without relying on business analysts or Project Managers.
- Thrives in a fast-paced environment, contributing to one of Asset Management’s most high-profile platforms.
- Operates as part of an agile team, regularly deploying software updates to production and adjusting to the dynamic needs and scale of the business.
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies.
- Provides regular technical guidance and direction to support the business and its technical teams, contractors, and vendors.
- Drives decisions that influence the product design, application functionality, and technical operations and processes.
- Serves as a function-wide subject matter expert in one or more areas of focus.
- 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.
- Contributes actively to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle.
- Develops secure and high-quality production code, and reviews and debugs code written by others.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience.
- Excellent programming experience in Core Java and SQL.
- Hands-on experience on SRE/ Support tooling like Splunk, Dynatrace, Servicenow.
- Experience in implementation of TDD and BDD techniques, with a focus on leveraging mocking frameworks for effective testing.
- Demonstrated understanding of IoC frameworks in Java, such as native Spring.
- Understanding of next generation messaging and streaming technologies such as Kafka, IBM MQ, Solace or Ignite.
- Good debugging skills with strong grasp of engineering principles, including CI/CD, application resiliency, and security.
- 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.
- Demonstrated knowledge of software applications and technical processes within a technical discipline (cloud, artificial intelligence, machine learning, etc.).
- Overall knowledge of the Software Development Life Cycle.
Preferred qualifications, capabilities, and skills
- Strong Hands-on exposure to AI development tools
- Excellent Debugging skill with SRE tooling experience
What you need to know about the Chennai Tech Scene
To locals, it's no secret that South India is leading the charge in big data infrastructure. While the environmental impact of data centers has long been a concern, emerging hubs like Chennai are favored by companies seeking ready access to renewable energy resources, which provide more sustainable and cost-effective solutions. As a result, Chennai, along with neighboring Bengaluru and Hyderabad, is poised for significant growth, with a projected 65 percent increase in data center capacity over the next decade.
