Qualifications

• An advanced degree in Computer Science, Data Science, Machine Learning, or a related field.
• Proven experience in building and deploying agentic AI applications in production environments.
• Expertise with machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.
• Proficiency in Python programming, including writing comprehensive tests and building evaluation harnesses for agents and prompts.
• Hands-on experience with agent frameworks such as LangChain, CrewAI, AutoGen, or LangGraph.
• Strong knowledge of generative models, including transformers, GANs, VAEs, and diffusion models.
• Understanding of data preprocessing, feature engineering, and evaluation techniques for models and agents.
• Familiarity with cloud platforms, containerization, and orchestration technologies.
• Excellent problem-solving skills with the ability to work independently and collaboratively in a team environment.
• Effective communication skills tailored to both technical and non-technical audiences.

Responsibilities

• Architect, develop, and operationalize autonomous and assistive AI agents aimed at enhancing business operations.
• Design comprehensive multi-agent systems, including role definitions, tool integrations, planning, memory management, and workflow orchestration using modern frameworks.
• Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search functionalities utilizing vector databases, including indexing, retrieval policies, and performance evaluation.
• Build and integrate agent tools and APIs to connect AI agents with external services, databases, and internal systems, ensuring robust output parsing and error handling mechanisms.
• Practice advanced prompt engineering techniques, incorporating output validation and guardrails to minimize hallucinations and ensure reliability.
• Design and implement microservices-based architectures, orchestrate multi-step workflows, and instrument agents for tracing, metrics collection, and feedback loops.
• Collaborate with stakeholders to gather requirements, design user-friendly human-AI interfaces, and deliver solutions that generate measurable business impact.
• Analyze data to improve agent capabilities, optimize retrieval processes, and support data-driven decision-making through A/B testing and performance assessments.
• Mentor team members on best practices related to agent frameworks, large language models, safety protocols, and development methodologies.

Benefits

Joining J.P. Morgan offers a competitive salary package complemented by comprehensive benefits, including health insurance, retirement plans, and wellness programs. Employees have access to ongoing professional development opportunities, including training, certifications, and participation in innovative projects that push the boundaries of technology in finance. The organization fosters a collaborative and inclusive work environment, encouraging diversity of thought and experience. Employees are empowered to grow their careers through mentorship, internal mobility, and leadership development initiatives. Additionally, the company emphasizes work-life balance, providing flexible work arrangements and resources to support personal well-being.

Equal Opportunity

J.P. Morgan is committed to fostering an inclusive and diverse workplace where all employees are valued and respected. We are an equal opportunity employer and do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability, or any other protected characteristic under applicable law. We also provide reasonable accommodations for applicants and employees with disabilities or religious practices, ensuring an equitable environment for all. Our commitment to diversity and inclusion is fundamental to our success and reflects our belief that diverse perspectives drive innovation and excellence.