What are the responsibilities and job description for the Sr Lead Software Engineer - Gen AI, Java FS/Python position at JPMorgan Chase?
Be an integral part of a team that drives cutting-edge generative AI solutions adding business value and enhance user experiences.
As a Senior Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking - Deposits Platform space, you play a crucial role in an agile team dedicated to enhancing, building, and delivering reliable, market-leading technology products in a secure, stable, and scalable manner. Your skills and contributions promote substantial business impact, and you leverage your deep technical expertise and problem-solving methodologies to address a wide range of challenges across various technologies and applications
Job responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- 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
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
- Adds to the team culture of diversity, opportunity, inclusion, and respect
- Designs and implements generative AI models including large language models, multimodal systems, and specialized domain-specific models.
- Builds scalable, robust AI infrastructure capable of handling enterprise-level workloads. Designs efficient data pipelines for model training and inference, implements MLOps practices for continuous integration and deployment, and ensure system reliability through comprehensive monitoring and testing frameworks.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5 years applied experience
- 5 years of hands-on experience in AI/ML development.
- Proficiency in Python, SQL, JavaScript/TypeScript, Go or Rust ML
- Proficiency in PyTorch, TensorFlow, and modern ML frameworks, Hugging Face Transformers, LangChain
- Experience in Infrastructure, AWS/Azure/GCP, Docker, Kubernetes, MLflow, Weights & Biases
- Deep understanding of transformer architectures, attention mechanisms, and neural network optimization techniques.
- Proven experience working with large language models including GPT, Claude, LLaMA, or similar architectures. Hands-on experience with fine-tuning techniques, prompt engineering, and model evaluation methodologies. Familiarity with vector databases, embedding models, and retrieval systems for RAG implementations.
- Demonstrated ability to deploy AI models in production environments with considerations for latency, throughput, and cost optimization. Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies. Understanding of model serving frameworks and API development.
- Advanced degree in Computer Science, Machine Learning, or related field
Preferred qualifications, capabilities, and skills
- Experience with distributed training and large-scale model development.
- Knowledge of AI safety, alignment, and responsible AI practices. Background in specific domains such as natural language processing, computer vision, or multimodal AI.. Contributions to open-source AI projects or published research in top-tier conferences.
- Experience in Vector databases (Pinecone, Weaviate), traditional databases (PostgreSQL, MongoDB)
- Experience in Tools & Platforms, Git, CI/CD pipelines, Jupyter notebooks, model serving platforms