Sumo Logic

Sales Engineer

• Partner with the MSSP Account Executives to understand customer challenges and mains, and articulate Sumo Logic’s value proposition, vision, and strategy to customers
• Technically close complex opportunities through advanced competitive knowledge, technical skill, and credibility
• Understand and help orchestrate all phases of the sales cycle, including leading technical validations during the Proof of Value phase
• Be successful working with all levels of an organization, from executives down to individual developers and Site Reliability Engineers
• Deliver product and technical demonstrations of the Sumo Logic service
• Work cross functionally with Product Management and Engineering to improve the Sumo Logic service based on your experience with customers

Sales Engineer, MSSP

Full-stack Engineer

• Designing and implementing extremely high-volume, fault-tolerant, scalable backend systems that process and manage petabytes of customer data.
• Work to improve algorithms built to schedule load on clusters of thousands of machines elastically at runtime.
• Improve systems to provide performance guarantees to customers in a shared-everything multi-tenant architecture.
• Lead and contribute to the re-architecting of our internal message processing technology to petabyte per day scale.
• Help manage exabytes of data using the latest and greatest technologies such as Kafka, Kubernetes and Docker.
• Work across Sumo interfacing with multiple teams including Search, Security and Metrics &amp; Tracing to identify requirements and architect solutions to meet their data core ingest needs.

Senior Software Engineer II – Core Ingest

Sales Development Rep

• Research, identify, and prospect new customer accounts within your assigned territory
• Book outbound meetings through cold calls, emails, social outreach, and targeted networking across multiple buyer personas (including Director, VP, and C-level)
• Qualify inbound and outbound leads and convert them into sales-ready opportunities
• Deliver relevant marketing content to prospective customers and promote marketing events.
• Leverage a modern prospecting tech stack including HockeyStack, LinkedIn Sales Navigator, ZoomInfo, Lusha, Outreach, Qualified, and more
• Partner closely with Account Executives to build and execute a shared territory plan-of-attack, ensuring the right message reaches the right prospects at the right time

Sales Development Representative

Research Engineer

• Conduct and lead both applied and original threat research, transforming intelligence, telemetry, and investigation into actionable detection logic for the Sumo Logic SIEM.
• Collaborate closely within Threat Labs to design, build, and refine detection content and validation pipelines that raise the bar for product and customer detection quality.
• Drive innovation in detection methodologies, including research activities such as malware analysis, infrastructure tracking, or honeypot operations, to discover new attacker behaviors.
• Publish and share findings — from detection logic to behavioral analysis and practical hunting guidance — that help customers maximize SIEM outcomes.
• Contribute to Threat Labs’ long‑term vision of a research‑driven, continuously evolving detection ecosystem built on practitioner insight and technical depth.
• Research, develop, and test threat detection logic in a lab environment, validating against real‑world attacker behaviors and ensuring technical alignment with Sumo Logic SIEM capabilities.
• Conduct original threat research, such as analyzing malware, tracking infrastructure, or experimenting with honeypots, and translate findings into detection opportunities.
• Investigate industry and adversary trends to identify emerging detection opportunities.
• Collaborate with product management and fellow Threat Labs engineers to scope and prioritize detection campaigns.
• Maintain and expand Threat Labs’ research lab infrastructure.
• Provide practitioner feedback to engineering and product management to inform feature design and roadmap decisions.
• Contribute to the security community through blogs, conference talks, open source projects, and public research contributions.

Staff Threat Research Engineer

Machine Learning Engineer

• Design, implement, and optimize agentic AI components, including tools, memory management, and prompts.
• Develop and maintain golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale.
• Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability.
• Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes.
• Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.
• Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.

Senior Machine Learning Engineer

Account Executive

• Land and expand new logo accounts. Treat existing customer base like new logos to drive incremental ARR growth within the account. Expand existing use cases and introduce new use cases to current buying centers.
• Measure and quantify the business value of our existing use cases and evangelize aggressively to new buying centers within each customer.
• Responsible for the full sales cycle of new, incremental and renewal business within the territory.
• Exude operational efficiency and forecast accuracy to run a best-in-class business.
• Up to 50% in-market travel to establish relationships. Be able to cultivate and grow relationships into referenceable champions.
• Provide timely and insightful input back to other corporate functions, particularly engineering, product management and marketing.

Enterprise Account Executive

Customer Success Manager

• Customer Retention and Expansion; forecasting; manage onboarding and adoption programs; develop sales tools & processes; create segmentation and coverage models.
• Facilitate QBRs (Quarterly Business Reviews); and maintain business metrics and reporting.
• Support Professional Services team via OpenAir; forecasting, bookings, KPIs.
• Validate, analyze, reconcile and summarize weekly, monthly, quarterly reports and metrics for leadership.
• Identify and resolve related data issues in SFDC, Gainsight, Clari, etc.
• Collaborate with business leaders and staff on analyzing reports and presenting findings.
• Identify and fulfill operational requirements in existing and new initiatives, including but not limited to process design, system changes, reporting, documentation and enablement.
• Identify and drive initiatives to streamline processes, reduce administrative overhead, and achieve business goals.
• Partner with leadership to define and adopt governance practices that support team and company objectives.
• Evaluate, pilot, and deploy AI and agentic solutions (e.g., AI-driven health scoring, automated playbooks, intelligent chatbots) to improve customer outcomes, accelerate time-to-value, and scale CS operations.
• Build and maintain an AI/automation roadmap for Customer Success, staying current with rapidly evolving technologies and proactively identifying opportunities to integrate them into existing workflows and customer touchpoints.
• Champion a data-driven culture by leveraging AI-powered analytics and predictive models to surface insights on customer health, churn risk, and expansion opportunities.

Director, Customer Success Operations

Technical Account Manager

• Help customers understand best practices
• Assist customers in navigating complexities of Sumo Logic
• Lead strategic growth through robust relationships
• Facilitate training on advanced features
• Identify financial and adoption risks
• Collaborate with the account team on strategies
• Monitor customer KPIs and deployment issues

Technical Account Engineer – Technical Account Manager, Technical Customer Success Manager

• Design, implement, and optimize agentic AI components, including context engineering, memory management, and prompts.
• Develop and maintain golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale.
• Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability.
• Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes.
• Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.
• Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.

• Target, manage and sell to a defined geographic territory with under 1,500 employees
• Own the full sales cycle, from prospecting to close, in order to fill Sumo Logic's pipeline
• Create and deliver accurate sales forecasts
• Perform product demos using web tools to prospect and customers
• Partner with internal resources to provide a stellar experience for prospective customers and ensure their needs are being met

Sales

• Partner with the Account Executives to understand customer challenges and mains, and articulate Sumo Logic’s value proposition, vision, and strategy to customers
• Technically close complex opportunities through advanced competitive knowledge, technical skill, and credibility
• Understand and help orchestrate all phases of the sales cycle, including leading technical validations during the Proof of Value phase
• Be successful working with all levels of an organization, from executives down to individual developers and Site Reliability Engineers
• Deliver product and technical demonstrations of the Sumo Logic service
• Work cross functionally with Product Management and Engineering to improve the Sumo Logic service based on your experience with customers

• Land and expand new logo accounts, with a focus on hunting and landing net new business. Treat existing customer base like new logos to drive incremental ARR growth within the account. Expand existing use cases and introduce new use cases to current buying centers.
• Measure and quantify the business value of our existing use cases and evangelize aggressively to new buying centers within each customer.
• Responsible for the full sales cycle of new, incremental and renewal business within the territory.
• Exude operational efficiency and forecast accuracy to run a best-in-class business.
• Up to 50% in-market travel to establish relationships. Be able to cultivate and grow relationships into referenceable champions.
• Provide timely and insightful input back to other corporate functions, particularly engineering, product management and marketing.

Enterprise Account Executive – Senior

• Design and implement scalable MLOps/LLMOps platforms supporting the full ML lifecycle: data versioning, model training, evaluation, deployment, and monitoring
• Build and maintain CI/CD pipelines for ML models and LLM applications with automated testing, validation, and rollback capabilities
• Develop infrastructure-as-code (IaC) for reproducible, version-controlled ML environments
• Architect model serving infrastructure with auto-scaling, A/B testing, and canary deployment capabilities
• Build platforms for LLM fine-tuning, prompt management, and experimentation at scale
• Implement evaluation frameworks for LLM performance, quality, safety, and cost optimization
• Design and deploy enterprise-grade AI agents and copilots with robust monitoring and guardrails
• Establish LLM observability: token usage tracking, latency monitoring, prompt/response logging, and cost attribution
• Own uptime, reliability, and performance of ML/LLM services (SLIs/SLOs)
• Implement comprehensive monitoring, alerting, and incident response for ML systems
• Participate in on-call rotations and drive post-incident reviews to improve system resilience
• Build automation and tooling to reduce toil and accelerate ML development velocity
• Partner with ML Engineers and Data Scientists to translate research into production-ready systems
• Collaborate with platform and infrastructure teams on cloud architecture and resource optimization
• Mentor team members on MLOps best practices, production ML patterns, and operational excellence
• Drive technical decisions on tooling, frameworks, and architectural patterns

Senior Machine Learning Engineer – MLOps, LLMOps

AI Engineer

• Lead and partner with fellow leadership members and teams on technical evaluation and adoption of cutting-edge agentic AI platforms, including Anthropic (Claude), LangChain/LangGraph, AWS Bedrock, and other emerging agent frameworks.
• Architect, prototype, and productionize multi-agent AI systems for Agentic SOC use cases, including detection, triage, investigation, and response workflows.
• Own the design of core agent architecture components, including planning, execution, tool orchestration, memory, context engineering, and long-running agent workflows.
• Lead AI agent evaluation systems, including offline and online evaluation pipelines, golden datasets, synthetic data generation, human- and LLM-based judging, and continuous quality monitoring.
• Drive LLM fine-tuning and alignment efforts to improve domain-specific reasoning, accuracy, and reliability for security and observability use cases.
• Design scalable LLMOps and AI agent infrastructure, including inference routing, latency optimization, cost control, and production observability for agent systems.
• Partner with product, security, and data platform leadership and teams to deliver end-to-end AI agent capabilities from prototype to customer-facing production systems.
• Lead and partner on technical direction and mentorship for AI engineers working on agentic AI and LLM systems.
• Define and implement best practices for AI safety, reliability, evaluation, and monitoring in production agentic systems.
• Operate as a senior technical owner in ambiguous problem spaces—setting technical direction, breaking down complex problems, and driving delivery across teams.

Staff Machine Learning Engineer – AI Tech Lead

Security Analyst

• Design, develop, and maintain internal controls in response to security and compliance goals: FedRAMP, SOC2, HIPAA, PCI-DSS, ISO27001, etc.
• Perform security reviews and identify security gaps in architecture resulting in recommendations for inclusion in the risk mitigation strategy
• Support tooling and automation that facilitate security and compliance related activities and lead to reducing the disruption of audit events
• Lead planning, coordination and execution of 3rd party-risk assessments and audits
• Develop and maintain internal and external-facing security and compliance documentation
• Work with product and engineering teams to maintain compliance baseline in Sumo Logic products
• Work with internal teams to formulate processes in line with compliance and security controls, hold them accountable for following them, and manage throughout Risk Treatment and Remediation plans
• Provide direction to management team on compliance goals and statuses
• Drive periodic reviews, updates, and maintenance of compliance items
• Interface with external auditors and be a primary point of contact for audits
• Participate in maintenance of standard security and compliance collateral for marketing and sales activities

Sales Engineer, MSSP

Senior Software Engineer II – Core Ingest

Sales Development Representative

Staff Threat Research Engineer

Senior Machine Learning Engineer

Enterprise Account Executive

Director, Customer Success Operations

Technical Account Engineer – Technical Account Manager, Technical Customer Success Manager

Senior Machine Learning Engineer

Account Executive

Sales Engineer

Enterprise Account Executive – Senior

Senior Machine Learning Engineer – MLOps, LLMOps

Staff Machine Learning Engineer – AI Tech Lead

Security Compliance Analyst