Software Engineer III - AI/ML

JPMorganChase•Houston, TX

16h

About The Position

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 Risk Technology organization, 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.

Requirements

Formal training or certification on software engineering concepts and 3+ years of applied experience.
Strong proficiency in Java (Java 11+) and Spring Boot for building enterprise-grade applications
Solid Python programming skills for ML/AI development and data processing, 3+ years of AI/ML experience.
Experience with RESTful API development, micro services architecture, and containerization (Docker, Kubernetes)
Hands-on experience with LLMs, prompt engineering, and at least one LLM orchestration framework (LangChain, LlamaIndex, or similar)
Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn) and integrating ML models into production systems
Experience with CI/CD pipelines, unit testing (JUnit, Mockito, pytest), and version control (Git)
Strong understanding of software engineering best practices and agile methodologies
Strong analytical and problem-solving skills with ability to work independently and collaboratively
Excellent written and verbal communication skills to convey technical concepts to diverse audiences

Nice To Haves

Experience with vector databases (Pinecone, Weaviate, Milvus, Chroma) and embedding models
Experience with Java-based data processing frameworks (Apache Spark, Apache Kafka, Apache Flink)
Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native AI/ML services (SageMaker, Azure ML, Vertex AI)
Knowledge of observability and monitoring tools for production ML systems (Prometheus, Grafana, DataDog)

Responsibilities

Develop and implement GenAI and Agentic AI solutions using Java and Python to enhance automation and decision-making processes
Design, deploy, and manage LLM-based solutions for various NLP tasks in the financial services domain, integrating with Java-based enterprise systems
Conduct research on prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning techniques to optimize model performance
Build RESTful APIs and microservices using Java and Spring Boot to expose ML models and AI capabilities to downstream applications
Collaborate with cross-functional teams including data scientists, engineers, and product owners to identify requirements and develop solutions to meet business needs
Build and maintain scalable data pipelines and ML workflows using Java-based frameworks and cloud services
Develop and maintain tools and frameworks for model training, evaluation, deployment, and monitoring
Implement MLOps best practices including model versioning, A/B testing, and continuous model evaluation
Ensure production-quality code with comprehensive unit testing using JUnit, Mockito, and integration testing frameworks
Communicate effectively with both technical and non-technical stakeholders, including senior leadership