We’re committed to putting people first – if you need an accommodation as you go through the job searching, application, and interviewing process, please click here for more information.
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A history of translating business requirements into technical designs. Agile engineering capabilities and a design-thinking mindset. Collaboration, adaptability, flexibility and the ability to manage time and prioritize work with a globally distributed development team. Well-developed oral and written communication skills for explaining your decision-making process to non-engineers. Leveraging AI/ML tools into software development, including integration, monitoring, and optimization. Proficiency in software engineering languages and tools, including Java, Spring Boot, AWS and RESTful services, spanning horizontal and vertical packages. 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Strong understanding of cloud technologies: AWS, Azure, Lambdas Experience with AWS Services such as API Gateway, DynamoDB, RDS, SQS, SNS and CloudWatch. Familiarity with API specifications (OpenAPI/Swagger). Experience with CI/CD tools/techniques & Dev Ops practices Strong understanding of architecture patterns: serverless, microservice, event-driven Strong programming discipline: unit testing, fault tolerance, data structures, complexity analysis, design patterns, etc. Extensive knowledge of IT concepts, strategies, methodologies and technical standards, cloud security and privacy policies Extensive understanding of backlog tracking, burndown metrics, and incremental delivery. 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Advocate for continuous improvement: performance tuning, technical debt reduction, and modernization efforts that enable international scale. Improve deployment cadence and reduce release risk through stronger CI/CD, automated testing, and observability. A minimum of five years of software engineering experience Domain experience in insurance, underwriting, or financial services (helpful but not required). Prior experience modernizing legacy systems or migrating monoliths to microservices. Experience in tech stack (React, NestJS, Aurora Progress, Github Actions, GraphQL, Typescript, Javascript) Experience with observability tools (Datadog, Splunk, etc.) and designing runbooks/incident response processes. 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Minimum 8+ years in Cybersecurity with 3+ years focused on securing AI/ML systems or GenAI applications in production. CISSP certification required Demonstrated deep technical experience designing secure architectures for: ML pipelines and MLOps platforms (data ingestion, feature stores, training, model registry, deployment, monitoring). GenAI workloads (LLM APIs, fine-tuning, RAG, vector databases, agent frameworks). Cloud-native environments (containers/Kubernetes, serverless, service mesh, VPC/network security). Strong knowledge of AI-specific threats and mitigations: data poisoning, model inversion/membership inference, model theft/IP protection, adversarial examples, prompt injection/jailbreaks, exfiltration via outputs, and LLM supply chain risks. Practical familiarity with security frameworks and standards: NIST AI RMF, OWASP Top 10 (including LLM apps), MITRE ATT&CK and ATLAS, or similar. Hands-on experience implementing: Identity and access controls for AI services (service principals, fine-grained IAM, token and key management). Secrets management (Vault, KMS/Key Vault/Cloud KMS/HSM), encryption-in-transit/at-rest, data tokenization, DLP. Monitoring/logging for AI systems (model telemetry, prompt/response logging with privacy controls, drift/anomaly detection). Demonstrated ability to quickly learn and build expertise in diverse and emerging technologies and new architectural concepts and principles Strong influencing and consensus building skills, and the adaptability to respond to change quickly Strong communications skills, both written and verbal Ability to effectively collaborate with all levels of the organization with diverse backgrounds Strong desire to drive change, and ability to adapt to change quickly Excellent communication skills; ability to influence architecture and risk decisions across engineering, product, and executive stakeholders. 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Participate in incident management events, provide consultative recommendations for resolutions, lead post-incident reviews, and drive remediation and resilience improvements. Maintain collaborative and strategic partnerships among customers, vendors, business partners, and technology teams; work closely with vendor teams supporting Guidewire PolicyCenter to ensure adherence to engineering, coding, and platform standards; solve complex engineering challenges across implementation domains. Break down complex problems into practical, operational solutions; manage multiple projects simultaneously while maximizing impact. Mentor staff to develop technical engineering capabilities; serve as a role model within the tech community and lead through hands-on technical contributions. 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