Lead Software Engineer Agentic AI Solutions , Java or Python
JPMorgan Chase4 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Develop, review, debug, and maintain secure, high-quality production code for data-intensive applications and platforms.
- Lead end-to-end design and implementation of complex software features from requirements through deployment and operational stability.
- Build and maintain agentic AI systems with multi-agent workflows, tool use, memory, multi-step reasoning, and human-in-the-loop controls.
- Implement LLM applications using RAG pipelines, embedding workflows, vector stores, and model-serving infrastructure.
- Own observability, evaluation, safety, prompt monitoring, output validation, cost tracking, and latency optimization for production AI systems.
- Drive technical decisions affecting application design, functionality, performance, reliability, and resiliency.
- Automate remediation of recurring issues and improve operational stability.
- Mentor junior and mid-level engineers, conduct code reviews, and share engineering best practices.
- Contribute to firmwide engineering frameworks, tools, SDLC practices, and AI-assisted development governance.
- Establish standards for validating AI-assisted engineering outputs for correctness, performance, security, and responsible use.
Requirements
- Formal training or certification in software engineering concepts and 10+ years of applied experience.
- Hands-on experience building and shipping LLM-based applications and agentic systems with tool use, memory, and multi-step reasoning in production.
- Advanced proficiency in 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 full Software Development Lifecycle.
- Strong understanding of agile methodologies, application resiliency, security best practices, and cloud-native engineering using AWS, Azure, or GCP.
- Experience leading enterprise-authorized AI-assisted software development practices and validating AI outputs for correctness, performance, and security.
- Understanding of responsible AI use, data sensitivity, secure input and output handling, and compliant usage controls.
- Preferred experience with LLM orchestration frameworks, model-serving infrastructure, AWS Bedrock, or Azure OpenAI.
- Preferred familiarity with AI evaluation, red-teaming, prompt drift detection, cost and latency monitoring, and constrained agentic design patterns.
- Preferred experience with Databricks, Snowflake, Spark, or PySpark and knowledge of financial services technology.
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.