Principal Software Engineer

Principal Software Engineer

Role overview

We are looking for a Principal Software Engineer to own the architecture and delivery of our platform - a modern, AWS-native ecosystem that powers underwriting intelligence, GenAI-driven analysis, and high-volume content processing pipelines. You will work across a rich stack of Python batch jobs, .NET APIs, PostgreSQL/Aurora, and LangGraph-based agentic services, taking end-to-end accountability for system quality, scalability, and reliability - with data as a core domain rather than the whole of the role.

This is a senior individual contributor role with meaningful technical leadership scope: you will set engineering standards, mentor engineers, coordinate across product and platform teams, and drive architectural decisions that shape how the platform moves from ingestion through transformation to AI-powered delivery.

Key responsibilities

• Architect and evolve the platform across ingestion, transformation, storage, API, and serving layers, ensuring fault tolerance and clear upgrade paths.
• Own end-to-end delivery of AWS Batch-based content loaders (Python 3.10), Lambda-based event-driven workflows, and service/API contracts (.NET 8 / REST / GraphQL).
• Drive decisions on Aurora PostgreSQL schema design, graph-structured data models, and OpenSearch indexing strategies used by GenAI retrieval.
• Define and enforce engineering and data quality standards, validation frameworks, and monitoring coverage across Pentaho, ThoughtSpot, CloudWatch, and Splunk.
• Partner with ML and product engineering to support LangGraph-based agentic RAG pipelines - ensuring the data and service layers (PostgreSQL, OpenSearch, SNS) are reliable, fresh, and optimally indexed for retrieval.
• Contribute to prompt data flows and evaluator pipelines (LLM-based testing), shaping how ground-truth datasets and synthetic test data are built and managed.
• Assess and validate AI-assisted engineering output with senior-level technical judgment before it reaches production.
• Write technical briefs and RFCs for significant architecture changes; gather feedback and drive decisions with documented trade-offs.
• Design and execute testing, rollout, monitoring, and rollback strategies for critical releases.
• Lead incident postmortems for production outages; track follow-up actions and improve operational resilience.
• Contribute to and evolve team engineering guidelines; ensure adoption through code reviews and working examples.
• Mentor engineers on software and data engineering best practices, design patterns, and agentic development discipline.
• Coordinate dependencies across multiple product squads, ensuring smooth handoffs and clear interface contracts.
• Communicate effectively with stakeholders on technical impacts, risks, and delivery timelines.

Requirements

• 6+ years of software engineering experience, with proven expertise building and operating production systems and data pipelines at scale.
• Strong software architecture and system design skills, with a track record of making and documenting significant technical trade-offs.
• Solid experience with .NET (C#) building production services and APIs; strong familiarity with REST and GraphQL patterns.
• Deep hands-on experience with AWS services: S3, Batch, Lambda, SNS, RDS/Aurora PostgreSQL, EKS, CloudWatch.
• SQL and PostgreSQL expertise, including schema design, query optimization, and graph-structured data modelling.
• Experience designing distributed, fault-tolerant systems with clear observability, rollback, and recovery strategies.
• Proficiency debugging complex issues across service boundaries using logs, metrics, and traces (Splunk, CloudWatch).
• Experience with CI/CD pipelines (Jenkins, GitHub Actions, or GitLab CI) and Agile delivery.
• Demonstrated technical leadership: mentoring, RFC/design-review authorship, and cross-team coordination.
• Excellent written and verbal communication skills; able to document complex technical decisions clearly.

Nice to have

• Python skills (3.10+) - including data transformation libraries such as Pandas, BeautifulSoup, and custom XML/HTML parsing.
• Hands-on experience with LangGraph, LangChain, or other agentic/LLM orchestration frameworks.
• Familiarity with vector search or OpenSearch for RAG pipelines.
• Experience with Kong Enterprise API Gateway or MCP (Model Context Protocol) integration patterns.
• Exposure to document conversion tooling (e.g., Aspose Word → HTML/XML) and unstructured data transformation.
• Experience with BI/reporting platforms such as ThoughtSpot or Pentaho.