Location: Hyderabad, Telangana, India

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As the AI/ML Lead Software Engineer at JPMorgan Chase within Business Banking, you will play a crucial role in designing and delivering cutting-edge AI technology products. You will define the AI-promoten validation roadmap and integrate comprehensive AI checks into campaign workflows across all channels. Your responsibilities include building AI/ML models to enhance pre-launch approvals, using external signals and trend analysis for actionable insights. Collaborating with Marketing, Legal, Compliance, and Controls, you will operationalize AI capabilities and standardize measurement across Consumer and Community Banking sub-lines of business. You will automate quality metrics, evolve the learning agenda, and provide executive-ready insights on the portfolio roadmap. Additionally, you will ensure seamless integration with systems to support transformation objectives and champion quality-as-a-service to promote continuous improvement. Your role will involve understanding and enhancing the end-to-end customer experience, leading architectural design sessions, and ensuring alignment with enterprise standards.
 

 

Job Responsibilities:

• Define the AI‑driven validation roadmap across Business Banking.
• Architect and embed end‑to‑end AI checks into campaign authoring and execution workflows for all channels.
• Build AI/ML models to enhance final reads (pre‑launch approvals), incorporating external signals and trend analysis to generate actionable recommendations.
• Partner with Marketing, Legal, Compliance, and Controls to operationalize AI capabilities and standardize measurement across  CCB sub‑LOBs.
• Automate quality metrics and evolve the learning agenda using internal benchmarks and external best practices.
• Provide executive‑ready insights, recommendations, and status updates on the portfolio roadmap and key learnings.
• Integrate with upstream and downstream systems to ensure seamless tooling and support Transformation objectives.
• Champion quality‑as‑a‑service: prevent errors and drive continuous improvement in validation processes.
• Demonstrate customer obsession by understanding and improving the end‑to‑end customer experience.
• Lead architectural design and review sessions, ensuring alignment with enterprise standards and best practices.

Required qualifications, capabilities and skills:

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Experience in one of the programming languages like Python, typescript, streamlit, UI design. Intermediate Python is a must.
• Strong background in Natural Language Processing (NLP) and Large Language Models (LLMs)
• Hands-on experience with machine learning and deep learning method & Experience of Gen AI builds, Agents, and MCP.
• Proficiency in AI and machine learning frameworks (e.g., TensorFlow, PyTorch).
• Strong programming skills in languages such as Python, R, or Java.
• Ability to design and implement complex algorithms for recommendation systems and trend analysis.
• Experience in data integration and real-time data processing & Understanding of marketing and campaign testing processes.
• Proven experience in architecting and designing large-scale AI/ML systems.
• Experience with DevOps practices and CI/CD pipelines for AI/ML deployments.

Preferred Qualifications:

• Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.
• Experience of all LLM models and their capabilities
• Experience with building and deploying ML models on cloud platforms such as AWS/Azure and AWS tools like Sagemaker, EKS, etc.
• Prior experience in credit card marketing and in-market testing.

• Excellent communication and presentation skills along with strong interpersonal skills and ability to translate technical concepts into actionable business strategies.

   

Carry out critical tech solutions across multiple technical areas as an integral part of an agile team