As a Software Engineer III, you will design and deliver technology solutions, develop production code, analyze data, and contribute to a diverse team culture.
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 JPMorgan Chase within the Employee Platforms team, you will be a seasoned member of an agile team, tasked with designing and delivering trusted, market-leading technology products that are secure, stable, and scalable. Your role involves implementing critical technology solutions across multiple technical domains, supporting various business functions to
Job responsibilities
Required qualifications, capabilities, and skills
Preferred qualifications, capabilities, and skills
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 JPMorgan Chase within the Employee Platforms team, you will be a seasoned member of an agile team, tasked with designing and delivering trusted, market-leading technology products that are secure, stable, and scalable. Your role involves implementing critical technology solutions across multiple technical domains, supporting various business functions to
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on practical experience in Python, SQL, advanced GenAI technologies like multimodality (Voice & Images), Agentic AI and ML technologies
- Highly proficient in coding in one or more languages such as Python, SQL, Java and R programming languages Experience with one or more platform tech stacks such as AWS, Docker, Kubernetes, Data bricks and CI/CD pipelines.
- Solid understanding of using ML techniques specially in Natural Language Processing (NLP), Knowledge Graph and Large Language Models (LLMs)
- Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search)
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Overall knowledge of the Software Development Life Cycle Solid understanding of agile methodologies such as CI/CD, application resiliency, and security
Preferred qualifications, capabilities, and skills
- Proficiency in optimizing and tuning AI models to ensure efficient, scalable solutions, with experience in building and deploying ML models on cloud platforms such as AWS and using tools like Sagemaker and EKS.
- Knowledge of data engineering practices to support AI model training and deployment, along with a strong understanding of machine learning algorithms and techniques-including supervised, unsupervised, and reinforcement learning-and hands-on experience with libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.
- Skills in collaborating with cross-functional teams to integrate generative AI solutions into broader business processes and applications, leveraging advanced LLM techniques such as Agents, Planning, and Reasoning.
- In-depth understanding of embedding-based search/ranking, recommender systems, graph techniques, and other advanced methodologies to enhance AI solution capabilities.
Top Skills
AWS
Ci/Cd
Databricks
Docker
Eks
Keras
Kubernetes
Python
PyTorch
Sagemaker
Scikit-Learn
SQL
TensorFlow
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