Sr Lead Software Engineer
JPMorgan Chase14 hours ago
Responsibilities
- Develop, review, debug, and ship secure, high-quality production code for data-intensive applications and platforms.
- Lead the end-to-end design and implementation of complex software features from requirements through deployment and operational stability.
- Build and maintain production agentic AI systems with multi-agent workflows, tool use, memory, multi-step reasoning, and human-in-the-loop controls.
- Implement LLM-based applications including RAG pipelines, embedding workflows, vector-store integrations, and model-serving infrastructure.
- Own observability, evaluation, safety, cost tracking, prompt monitoring, output validation, and latency optimization for production AI systems.
- Drive technical decisions affecting application design, performance, functionality, reliability, and security.
- Automate remediation of recurring issues and improve operational stability.
- Mentor junior and mid-level engineers through coaching, code reviews, and engineering best practices.
- Promote firmwide frameworks, tools, SDLC practices, approved AI-assisted engineering, governance, validation standards, and reusable automation patterns.
Requirements
- Formal training or certification in software engineering concepts and at least 5 years of applied experience.
- Hands-on experience building and shipping production LLM-based applications and agentic systems with tool use, memory, and multi-step reasoning.
- Advanced proficiency in one or more programming languages, particularly Python and/or Java.
- Deep experience with large-scale data processing, microservices, API design, and Kafka-based event streaming.
- Working knowledge of relational and NoSQL databases, vector stores, and data lake architectures.
- Experience with Redis, MemCached, Dynatrace, Splunk, Grafana, Airflow, and Temporal.
- Proficiency in CI/CD, test-driven development, automation, and the Software Development Lifecycle.
- Strong understanding of agile methodologies, application resiliency, security best practices, responsible AI, data sensitivity, and secure input/output handling.
- Practical cloud-native engineering experience with AWS, Azure, or GCP.
- Experience leading enterprise-authorized AI-assisted software development and validating AI outputs for correctness, performance, and security.
- Preferred experience with LLM orchestration frameworks, AWS Bedrock, Azure OpenAI, AI evaluation and observability, red-teaming, prompt drift detection, Databricks, Snowflake, Spark, and PySpark.
- Knowledge of financial services, AI risk, and regulatory considerations for AI in financial decision-making.
Benefits
- Competitive total rewards package with base salary determined by role, experience, skills, and location; eligible roles may also receive incentive compensation.
- Comprehensive health care coverage and on-site health and wellness centers.
- Retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching.
- Additional benefits and total compensation details are provided during the hiring process.
Tech Stack
Apache AirflowApache KafkaApache SparkAWSAzureDatabricksGoogle Cloud PlatformGrafanaJavaPythonRedisSnowflakeSplunk
Categories
About JPMorgan Chase
JPMorgan Chase provides consumer and commercial banking, payments, credit card, wealth management, and corporate and investment banking services to individuals, businesses, institutions, and governments. The public company (NYSE: JPM) earns revenue from interest, fees, trading, and asset management across operations in more than 100 markets. Headquartered in New York City with roots dating to 1799, it serves retail customers and prominent corporate and government clients through brands including Chase and J.P. Morgan.