Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorgan Chase within the Engineer's Platform & Integrated Experience (EPIX) organization, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications. For this role you will build and deploy cutting edge Generative AI RAG and Agentic systems to augment processes for the software development lifecycle (SDLC) across the firm.
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, equity, inclusion, and respect Deploy LLMs, Vector datastores, and RAG systems as a service with scalability and security requirements Design, implement and deploy scalable data pipelines on distributed compute platforms Deploy and operate Generative AI benchmarking systems to advance the firm's understanding of various LLM and Agentic system capabilities Evaluate Generative AI Products and procure into JPMC following proper firmwide standards and control policies
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 Advanced in one or more programming language(s): Python, Go, Javscript, Java Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Ability to tackle design and functionality problems independently with little to no oversight Practical cloud native experience Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field Highly capable with Kubernetes, Helm, Docker and container based application deployments Strong experience with enabling and executing distributed compute for data engineering and AI/ML training/fine tuning Experience with AI/ML Ops tools, experiment tracking, model lifecycle and governance best practices Experience with open-source frameworks: Ray, Spark, PyTorch, LlamaIndex, LangChain
Preferred qualifications, capabilities, and skills
Experience with Vector datastores, Chroma, Elastic, DeepLake Some experience with NLP projects using prompt engineering, prompt based learning, Chain-Of-Thought techniques Knowledge of various LLM fine tuning techniques: SFT, RLHF, DPO, Lora, Quantization