• Work independently with cross-functional teams to develop software and system requirements. • Lead major architectural updates to the perception stack, including system-level design, modularization, and migration strategies that improve scalability, latency, and maintainability across the fleet. • Design, develop, and own scene detection and activation capabilities, classifying the operating scene/scenario and triggering the appropriate perception behaviors and operational design domain (ODD) logic at runtime. • Improve perception robustness under degradation and adverse weather, including sensor fault detection, health monitoring, graceful degradation, and fallback strategies for rain, snow, fog, glare, low-light, and sensor soiling/occlusion conditions. • Design, implement, and test state-of-the-art perception features on time with high quality, industrial-grade production code. • Integrate large-scale multi-modal models (including but not limited to VLMs and LLMs) into the perception stack to improve semantic scene understanding and reasoning. • Track and trend technical performance of perception in the field. • Lead major feature development including feature design, code reviews, issue diagnosis, and resolution. • Lead extensive testing to validate features and satisfy release schedules. • Lead development related to data, development, and ML pipelines, specifically focused on multimodal data alignment for training foundation models.

Role Description We are seeking an energetic, passionate individual with strong communication skills and the ability to work collaboratively. You are a self-starter who thrives in an environment of personal accountability and enjoys being part of a challenging outcome-oriented culture. You want to build your career by digging in, being a part of a high-performance team where there is an opportunity to up your game, sharing your knowledge and working with some of the best in the business. You’ll design, deploy, and operate scalable Elastic (Elasticsearch, Logstash, Kibana) environments that power cybersecurity analytics, threat hunting, and data-driven detection use cases. You’ll own reliable log ingestion pipelines, optimize cluster performance, and turn technical outcomes into clear insights for both technical and non-technical stakeholders. Key Responsibilities: - Design and operate distributed Elastic clusters, including capacity planning, performance tuning, and scaling strategy - Build and maintain ingestion pipelines aligned to security frameworks and Elastic Common Schema (ECS) - Manage large-scale Elastic Agent and Fleet deployments - Serve as the SME for log ingestion, parsing, normalization, and analysis - Deliver Elastic infrastructure as code (IaC) and automate deployments/configuration where possible - Develop and maintain Logstash pipelines (e.g., Syslog and other structured/unstructured sources) - Integrate multiple data sources and third-party platforms into Elastic with clean, searchable data models - Create automation/scripts to detect anomalies and improve operational workflows - Build dashboards, visualizations, and investigation workflows in Kibana - Continuously improve reliability and efficiency by optimizing pipelines, automating manual work, and enhancing architecture - Support development of network intrusion analytics in collaboration with a broader detection/engineering team - Administer supporting Linux systems for Elastic components and data pipeline services Qualifications - Certified Elastic Engineer - Ability to configure, maintain, and troubleshoot multiple Elastic environments at on-premises and Elastic-Cloud. - Experience with Elastic Stack architecture, design, and deployment. - Deep understanding of Elasticsearch internals, including indexing, search, and data aggregation. - Skills in managing enterprise level Elasticsearch clusters, handling cluster health, performance tuning, scaling, and ensuring high availability. - Proficiency in Elasticsearch Query DSL for complex queries, aggregations, and data analytics. - Proficiency in programming languages such as Java, Python, or Ruby. Knowledge of scripting languages for automation is also beneficial. - Proven track record working in cybersecurity, understanding common attack vectors, threat landscapes, and defensive technologies. - Proficiency in implementing security measures within Elasticsearch, such as role-based access control, encryption, index security, and audit logging. - Skills in managing and analyzing logs and security events from various sources (firewalls, IDS/IPS systems, network devices, operating systems) using the ELK stack. - Advanced ability to craft complex queries, alerts, and visualizations tailored for cybersecurity needs, such as detecting anomalies and potential threats. - Proficiency in data parsing using GROK/DISSECT, ingestion, and ETL workflows. - Expertise in developing complex Elasticsearch Watchers. - Experience in Elastic Security, Detection Rules, Machine Learning and AI Assistant. - Proficiency in developing Elasticsearch solutions to specific security needs, such as custom dashboards and reports for ongoing monitoring. Benefits - Competitive compensation package & benefits package - Company events, recognitions, and celebrations - Career development and growth opportunity Company Description At Jolera, we are committed to creating a diverse, equal and inclusive environment. Our goal is to attract and retain the best talent while embracing diversity in all its forms. We value and respect differences in ethnic background, gender, age, religion, identity, disability, or any other characteristic protected by applicable law.

• Embed with enterprise retail customers and partners to understand their technical environments, data systems, and business workflows. • Design, build, and deploy AI and agentic solutions tailored to each customer's specific infrastructure and needs, across Instacart's full platform suite. • Extend, adapt, and integrate Instacart's core AI capabilities to fit customer ecosystems, even when those systems are undocumented or non-standard. • Maintain a close working relationship with R&D: participate in product reviews, flag platform gaps encountered in the field, and propose concrete changes that would make the platform work better for enterprise customers. • Collaborate closely with the AI Solutions Architect to translate domain requirements and architecture into working software. • Serve as the primary technical point of contact for customers during implementation engagements.

• Embed with enterprise retail customers and partners to understand their technical environments, data systems, and business workflows. • Design, build, and deploy AI and agentic solutions tailored to each customer's specific infrastructure and needs. • Extend, adapt, and integrate Instacart's core AI capabilities to fit customer ecosystems. • Maintain a close working relationship with R&D. • Collaborate closely with the AI Solutions Architect to translate domain requirements and architecture into working software. • Serve as the primary technical point of contact for customers during implementation engagements.