Full Stack Senior Lead Software Engineer

Be an integral part of an agile team enhancing, building, and delivering advanced technology products.

As a Senior Lead Software Engineer within JPMorgan Chase’s Corporate Technology division, you will play a key role in designing and implementing innovative business features powered by Agentic and Generative AI frameworks.

• Develop and implement generative AI solutions that meet technical and business requirements.
• Lead the creation of proofs of concept (POCs) to explore and validate new AI approaches.
• Integrate AI solutions with AWS, ensuring quality, security, and efficiency.
• Identify and automate processes to improve operational stability of AI systems.
• Collaborate with cross-functional teams to refine AI system architectures for scalability and reliability.
• Participate in communities of practice to stay current with generative AI advancements.
• Support a team culture that values diversity, inclusion, and respect.
• Contribute to the evaluation and adoption of new AI tools and frameworks.
• Ensure compliance with organizational standards and regulatory requirements in AI projects.
• Mentor and guide junior engineers in AI development best practices.
• Document technical solutions and share knowledge with the team.

• Bachelor’s degree in Computer Science, Engineering, or related field, with 5+ years of software engineering experience.
• Proficiency in Python or Java, with experience building AI models, including large language models (LLMs).
• Hands‑on experience in generative AI development and prompt engineering.
• Background in system design, application development, testing, and maintaining operational stability in AI projects.
• Experience with AWS cloud services and Terraform.
• Experience working with LLM models and agentic AI tools.
• Familiarity with agile methodologies, including CI/CD, application resiliency, and security practices.
• Strong problem‑solving and analytical skills.
• Effective communication and teamwork abilities.
• Ability to manage multiple priorities in a fast‑paced environment.
• Commitment to continuous learning and professional development.

• Experience optimizing and tuning AI models for performance and scalability.
• Familiarity with Open Search and vector embeddings.
• Understanding of data engineering practices for AI model training and deployment.
• Experience integrating generative AI solutions into business processes and applications.
• Experience with AI/ML libraries and tools such as Langchain, PyTorch, Scikit-learn, and Keras.
• Advanced degree in a related field.
• Experience with cloud‑based AI deployment and monitoring.