12 hours ago
Kraków, PolandStaff+
Responsibilities
- Shape platform architecture across ingestion, transformation, storage, APIs, and AI-powered services.
- Own delivery of AWS Batch content pipelines, Lambda workflows, and .NET REST/GraphQL APIs.
- Drive architecture decisions involving Aurora PostgreSQL, graph-based data models, OpenSearch, and GenAI retrieval.
- Define engineering, data quality, testing, observability, rollout, monitoring, and rollback standards.
- Partner with ML and Product Engineering teams on LangGraph-based RAG pipelines and LLM evaluation data pipelines.
- Review and validate AI-assisted engineering output before production deployment.
- Lead technical briefs, RFCs, design reviews, architecture decisions, incident reviews, and postmortems.
- Mentor engineers in software architecture, data engineering, design patterns, and responsible AI-assisted development.
- Coordinate technical dependencies across product squads and communicate technical risks and decisions to stakeholders.
Requirements
- Extensive software engineering experience building and operating production systems and data pipelines at scale.
- Strong software architecture and system design expertise, including complex technical trade-offs.
- Advanced production experience with .NET/C#, REST, and GraphQL services and APIs.
- Deep AWS experience with S3, Batch, Lambda, SNS, RDS/Aurora PostgreSQL, EKS, and CloudWatch.
- Strong SQL and PostgreSQL expertise, including schema design, query optimization, and graph-based data modeling.
- Experience designing distributed, scalable, and fault-tolerant systems with observability, recovery, and rollback strategies.
- Strong troubleshooting experience using logs, metrics, and traces with Splunk and CloudWatch.
- Experience with CI/CD and Agile delivery using Jenkins, GitHub Actions, or GitLab CI.
- Demonstrated technical leadership through mentoring, design reviews, RFCs, and cross-team coordination.
- Excellent written and verbal communication skills.
- Python 3.10+ experience, including Pandas, BeautifulSoup, and XML/HTML processing, is a nice-to-have.
- Experience with LangGraph, LangChain, other LLM/agentic frameworks, OpenSearch, or vector search technologies is a nice-to-have.
Benefits
- Hybrid work model with flexible working hours.
- Private health insurance and medical care.
- Multisport card and sports and wellness programs.
- Professional development programs, well-being initiatives, team-building events, paid vacation, and sick leave in line with the Polish Labour Code.
Tech Stack
Categories
BackendData Engineering
About Verisk
Verisk builds data analytics platforms, predictive models, and software used by property and casualty insurers to underwrite, price, detect fraud, and manage claims. The company monetizes industry-scale datasets, catastrophe risk models, and workflow tools sold by subscription and transaction to insurers, reinsurers, and brokers worldwide. Founded in 1971 and headquartered in Jersey City, New Jersey, Verisk is a public company trading on Nasdaq (VRSK).