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our Labs is where innovation meets impact. As the technological powerhouse behind our company, we design and build cutting-edge solutions that revolutionize the insurance industry. Whether its Real-Time claims payments or predictive analytics, our Labs team is at the forefront of driving change and shaping the future of insurance. Ready to innovate with us? We are looking for a FinOps Manager to lead cloud and AI cost optimization, improve financial accountability, and maximize the value of our cloud and AI/ML workloads. This role works across Engineering, DevOps, data, AI/ML, Finance, and Leadership to drive visibility, efficiency, and governance in both cloud infrastructure and AI consumption and will be reporting directly to the VP of IT Infrastructure.
Responsibilities Cloud & AI Cost Optimization
* Own and evolve the organizations FinOps and AIOps cost strategy
* Monitor and optimize spend for:
* Cloud compute, Storage, networking
* SaaS AI services (e.g., OpenAI, Vertex AI, Bedrock, Azure OpenAI)
* Provide actionable recommendations for model selection, right-sizing, and inference optimization. Reporting & Governance
* Build dashboards for Real-Time visibility into cloud and AI cost drivers.
* Implement cost allocation models for training vs. inference, environments, and business units.
* Define tagging standards, budgeting processes, and consumption guardrails.
* Track unit economics such as cost per inference, cost per model training run, and per-product AI usage. Cross-Team Collaboration
* Partner with engineering, data /AI teams, and finance to plan and forecast cloud & AI consumption.
* Guide teams in designing efficient architectures and model deployment strategies
* Educate stakeholders on cost-aware engineering and AI usage best practices.

As a Support Engineer, you will be an integral part of our elite technical support organization, collaborating with a global team of experts across Engineering, QA, Security, and Product Support.

In this role, you will leverage a diverse skill set, including:
Serve as a trusted technical advisor, ensuring customer satisfaction and solution effectiveness.
Communicate clearly with both technical and non-technical stakeholders.
Document solutions, procedures, and known issues for internal and customer use.
Analyzing source code, log files, dump files, and network/endpoint traces to diagnose field-related product issues.
Enhancing internal tools and contributing to both internal and external Knowledge Base articles.
Troubleshooting complex technical challenges, documenting resolution methodologies, and sharing knowledge with the Support team to enhance their expertise.
Identifying product bugs and improvement opportunities, coordinating with development teams, and prioritizing resolutions to ensure a seamless customer experience.
Driving product quality forward, either independently or by facilitating cross-functional collaboration within the organization.

We are currently seeking a Python Developer - LLM & MCP Integration to contribute to the success of our rapidly growing business.

This role focuses on building backend services and LLM-integrated functionality that plug into our existing MCP platform, enabling advanced AI-driven product capabilities across our security offerings.

As a Python Developer - LLM & MCP Integration, you will:
Build and maintain Python-based backend services that integrate with the MCP platform.
Own the end-to-end data and logic pipeline behind these AI-powered capabilities.
Design and maintain Vector Database ingestion pipelines for product documentation and knowledge content.
Normalize and structure security events to support accurate LLM explanations and summaries.
Ensure solutions meet our security, scalability, and reliability standards.

Cybersecurity system architect We are a global leader in high-scale, disaggregated networking solutions, redefining how the worlds largest service providers and hyperscalers build their infrastructure.
As a Cybersecurity system architect, you will join our core R&D Architecture group to define the end-to-end security fabric of our platforms. You will lead the integration of deep security intelligence into high-performance, telecom-grade network operating systems.

Responsibilities:
Define Security Architecture: Lead the design of L3-L7 firewalling, stateful inspection, and application-aware filtering.
Threat Detection Frameworks: Architect scalable engines for DPI (Deep Packet Inspection), signature/anomaly detection, and ML-based threat mitigation.
system Integration: Conduct system -level threat modeling and define secure communication paths across platform and protocol layers.
Performance Optimization: Align security enforcement with hardware-assisted offload strategies to ensure line-rate performance with minimal latency.
Collaboration: Work closely with R&D teams to embed behavioral analytics and evasion-resilient detection into the product's core.