Principal Software Engineer
On-siteJersey City, New Jersey, United States
Job Summary
Architect and implement complex, scalable engineering frameworks using modern software design principles to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Develop secure, high-quality production code for data-intensive applications while designing and governing agentic AI systems, including multi-agent workflows and tool-use integrations appropriate for regulated financial services environments. Establish engineering standards for LLM-based applications, ensuring safety, observability, and reproducibility at scale, and serve as the function's go-to subject matter expert in data engineering, platform architecture, or AI systems. Advise cross-functional teams on technological matters and influence leaders on technical strategy and direction.
Required Qualifications
- Formal training or certification on software engineering concepts
- 7+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale
- Hands-on experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures with tool use, memory, and multi-step reasoning in regulated environments
- Expert in one or more programming languages, particularly Python and/or Java
- Advanced knowledge of software application development and technical processes, with considerable depth in one or more disciplines (e.g., cloud, AI/ML, data engineering)
- Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)
- Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance
- Practical cloud-native experience (AWS, Azure, or GCP)
- Ability to present and effectively communicate with senior leaders and executives
- Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
- Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data
- Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse
Desired Qualifications
- Experience with LLM orchestration frameworks and model serving infrastructure or managed endpoints (AWS Bedrock, Azure OpenAI)
- Familiarity with AI evaluation and observability practices: evals frameworks, red-teaming, prompt drift detection, and cost/latency monitoring for LLM workloads
- Understanding of agentic design patterns and how to constrain agent autonomy in high-stakes financial workflows
- Experience with modern data platforms such as Databricks or Snowflake
- Deep hands-on experience with Spark/PySpark and other big data processing technologies
- Expertise in open-source table formats and catalog services such as Apache Iceberg
- Awareness of AI risk and regulatory considerations relevant to AI use in financial decision-making
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.