Director of Software Engineering

• Business Unit Consumer & Community Banking
• Locations Parcel 9, Embassy Tech Village, Outer Ring Road, Deverabeesanhalli Village, Varthur Hobli, Bengaluru, IN-KA, 560103, IN
• Job Schedule Full time

Job Description

Elevate your career by steering multi-faceted tech programs, integrating innovative solutions for a dynamic impact across global operations.

As an Executive Director, Director of Software Engineering at JPMorgan Chase within the Consumer and Community Banking division for our AI/ML platform, your role will encompass leading the design and development of our robust, scalable, and high-performance AI/ML platform. You will be responsible for managing and expanding a team of skilled engineers and AI specialists, while promoting a culture of innovation and continuous enhancement. In collaboration with product management and cross-functional teams, you will contribute to defining the product vision, roadmaps, and deliverables for AI-promoten features and capabilities. Together, we will promote the adoption of best practices in software engineering, machine learning operations (MLOps), and data governance, ensuring compliance with data privacy and security regulations. You will supervise the complete lifecycle of AI/ML projects, from ideation and development to deployment and maintenance, while effectively communicating technical concepts and solutions at all levels of the organization. Additionally, you will manage budgets, allocate resources efficiently, and report on progress and challenges to executive leadership. Leveraging your advanced knowledge in AI/ML, software engineering, and cloud-native experience, you will play a pivotal role in keeping us at the forefront of industry trends and technological advancements.

Job Responsibilities

Lead the design and development of our AI/ML platform, ensuring robustness, scalability, and high performance.

Manage and grow a team of talented engineers and AI specialists, fostering a culture of innovation and continuous improvement.

Collaborate with product management and cross-functional teams to define product vision, roadmaps, and deliverables for AI-driven features and capabilities.

Drive the adoption of best practices in software engineering, machine learning operations (MLOps), and data governance.

Stay abreast of emerging trends and technologies in artificial intelligence and machine learning, and assess their applicability to business goals.

Ensure compliance with data privacy and security regulations pertinent to AI/ML solutions.

Oversee the end-to-end lifecycle of AI/ML projects, from ideation and development to deployment and maintenance.

Communicate technical concepts and solutions effectively at all levels of the organization.

Manage budgets, allocate resources efficiently, and report on progress and challenges to executive leadership.

Required Qualifications, Capabilities, and Skills

Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise.

Advanced knowledge in software engineering, AI/ML, machine learning operations (MLOps), and data governance.

Experience developing or leading large or cross-functional teams of technologists.

Demonstrated prior experience influencing highly matrixed, complex organizations and delivering value at scale.

Experience leading complex projects supporting system design, testing, and operational stability.

Experience with hiring, developing, and recognizing talent.

Extensive practical cloud-native experience.

Expertise in computer science, computer engineering, mathematics, or a related technical field.

Preferred Qualifications, Capabilities, and Skills

In-depth understanding of search/ranking, recommender systems, RAG (similarity search), graph techniques, and other advanced methodologies.

Understanding of large language model (LLM) techniques, including agents, planning, reasoning, and other related methods.

Expertise in training and fine-tuning large language models (LLMs) and embedding models, including advanced knowledge in the areas of LLM operations (LLM Ops) and AI operations (AIOps).