TigerData (creators of TimescaleDB)

• Triage, validate, and remediate security vulnerabilities across products, infrastructure, and internal systems. • Develop, maintain, and contribute to internal and open-source security tooling. Read and write production-grade code. • Improve secure development practices: perform secure code reviews, threat modeling, and security design reviews. • Improve security automation across CI/CD, cloud, and internal platforms. • Support incident response, security investigations, and compliance initiatives (evidence gathering, access reviews). • Investigate emerging risks related to AI-assisted development and actively use AI tooling in workflows.

• Leading the design and development of TimescaleDB Enterprise, our on-prem deployment and management platform for TimescaleDB. • Building and evolving core product capabilities, including: - management consoles, - deployment workflows, - operational tooling, - configuration management, - and customer administration experiences. • Owning technical decisions across the product lifecycle, balancing speed, scalability, maintainability, and customer experience. • Working directly with enterprise customers and prospects to understand operational requirements and translate them into pragmatic product solutions. • Driving new feature development while continuously improving reliability, usability, and operational simplicity. • Partnering closely with Platform Engineering and cross-functional stakeholders across Product, Support, and Sales Engineering. • Helping shape the long-term product and technical direction of the Enterprise platform. • Operating effectively in ambiguous environments where priorities evolve quickly and engineers are expected to drive clarity. • Leveraging AI tools daily to accelerate development, debugging, documentation, and product iteration workflows.

• Own the hardest part of customer adoption. Ship real results, fast. • Provide customer project delivery. • Implement migrations, data optimizations, and schema designs. • Scope and execute engagements with clear, measurable deliverables. • Fix complex technical problems. • Tune slow queries and configurations. • Write tactical fixes and scripts to unblock customers quickly. • Apply AI to accelerate engineering. • Use copilots (LLMs, AI assistants) to generate query rewrites and test optimizations. • Create reusable AI prompts and delivery playbooks. • Bridge architecture and reality. • Translate reference architectures into customer-specific deployments. • Adapt TigerData features (e.g., Hypertables, Hypercore, continuous aggregates, vector search) to real workloads. • Be the customer’s technical champion. • Own technical success during project delivery. • Escalate to core Engineering only when there’s a product-level gap. • Capture and share knowledge. • Write playbooks, scripts, and internal guides. • Feed learnings back to Product and Engineering.

• Maintain stability of control plane consisting of a distributed microservice architecture closely interacting with kubernetes and cloud provider APIs • Debug and resolve complex Kubernetes issues across multiple regions and clouds • Automate database lifecycle operations (deploy, resize, upgrade, fork) • Participate in on-call rotation, handle incident response, perform root cause analysis • Develop back-end features for Tiger Cloud, specializing in a distributed microservice architecture • Develop Kubernetes controllers, operators, and CRDs to extend platform capabilities • Enhance observability and monitoring systems • Improve deployment reliability, error handling, and client tooling (CLI interfaces) • Collaborate closely with infrastructure and software engineering teams • Stay current with Kubernetes releases and contribute to system architecture of scalable microservices

• Leading Tiger Data’s Customer Success and Technical Support organizations, including managers and highly technical customer-facing teams. • Building and operationalizing Tiger Data’s customer experience strategy for our next phase of growth, especially as we expand into larger enterprise accounts. • Partner to define clear ownership across Customer Success, Technical Support, Pre-Sales, Implementation, Sales, Product, and Engineering so customers experience one Tiger Data team, not internal handoffs. • Designing customer segmentation, engagement models, escalation paths, support coverage, success planning, health scoring, and renewal/expansion motions that scale. • Driving measurable improvements in adoption, retention, gross revenue retention, net revenue retention, expansion, customer satisfaction, time-to-resolution, support quality, and executive visibility into customer health. • Acting as the executive voice of the customer internally, turning customer trends, escalations, support patterns, and adoption signals into clear recommendations for Product, Engineering, GTM, and company leadership. • Building the next generation of customer operating rhythms: QBRs/EBRs, escalation reviews, customer health reviews, renewal risk reviews, expansion planning, support quality reviews, and executive customer reporting. • Coaching and developing managers while staying hands-on enough to understand the reality of the team’s work, customer pain points, and operational gaps. • Using AI thoughtfully to improve the customer experience and team productivity, including support workflows, knowledge management, customer health insights, escalation analysis, team enablement, and customer communication quality. • Hiring, developing, and retaining high-performing customer leaders and individual contributors who can operate with urgency, technical curiosity, ownership, and customer empathy. • Building systems and processes that make the team sharper, faster, and more accountable, without slowing down the startup pace that makes Tiger Data work.

• Owning the technical side of deals by helping move customers from “this looks interesting” to “we’re confident this will work.” • Working directly with customers to design scalable systems using PostgreSQL and TigerData • Going deep on real problems: schema design, query optimization, performance issues, and architectural tradeoffs • Acting as a trusted technical partner from the first conversation through early adoption • Collaborating closely with Product, Engineering, Support, and Customer Success - bringing real customer feedback back into the product • Building things that scale your impact: demos, reference architectures, benchmarks, and technical content • Using AI tools where they actually help - whether that’s analyzing queries faster, exploring architectures, or speeding up how you build and share solutions • Staying curious and continuously learning (Postgres ecosystem, cloud infra, emerging data patterns, etc.)

• Owning full-cycle recruiting for engineering roles across the business, from intake and calibration through sourcing, interview process design, offer, and close • Maintaining a high bar for every hire. We are a small organization, and every hire can make a positive or negative impact on our goals. This responsibility cannot be taken lightly. • Partnering closely with hiring managers to define role scope, align on candidate profile, and build practical, high-signal interview plans • Coaching interviewers and hiring teams on structured interviewing, candidate evaluation, and how to maintain a high hiring bar while moving with urgency • Personally driving outbound sourcing strategy and execution across multiple roles; we do not have dedicated sourcers, so this role is expected to source heavily and consistently • Managing candidate pipelines with intensity and precision, ensuring strong conversion at every stage from first outreach through offer acceptance • Creating an excellent candidate experience, especially with high-demand engineering talent who expect responsiveness, clarity, and strong selling throughout the process • Using AI tools effectively to improve recruiter productivity, sourcing research, communication quality, interview preparation, and pipeline management, while applying sound judgment and maintaining a high-quality candidate experience

• Own developer-facing messaging, competitive intelligence, and feature-level launches for Tiger Cloud. • Craft technically accurate narratives for developers. • Drive end-to-end GTM for feature releases, including positioning and content. • Build and maintain competitive positioning materials and battle cards. • Produce high-quality, developer-first content including blogs and landing pages. • Partner with Demand Generation and Marketing Operations for product stories. • Contribute to technical demo materials and field-facing messaging.

• Prospect to CTOs, Engineering Leaders, and technical end users with insight-led outreach that challenges how they currently approach their problems. • Take ownership of Sales Qualified Leads (SQLs) by shaping the deal, not just progressing it. • Diagnose customer challenges and reframe them in a way that highlights risks, hidden costs, and missed opportunities in the status quo. • Manage the full sales cycle, confidently guiding stakeholders toward clear decisions. • Lead multi-stakeholder sales processes, tailoring your message to technical and business audiences. • Leverage Solutions Architects, Customer Success, and Support strategically. • Take control of deal strategy, next steps, and timelines to consistently close high-quality opportunities.

• Deliver customer projects • Implement migrations, data optimizations, and schema designs • Scope and execute engagements with clear, measurable deliverables • Fix complex technical problems • Tune slow queries and configurations • Write tactical fixes and scripts to unblock customers quickly • Apply AI to accelerate engineering • Use copilots (LLMs, AI assistants) to generate query rewrites and test optimizations • Create reusable AI prompts and delivery playbooks • Bridge architecture and reality • Translate reference architectures into customer-specific deployments • Adapt TigerData features (e.g., Hypertables, Hypercore, continuous aggregates, vector search) to real workloads • Be the customer’s technical champion • Own technical success during project delivery • Escalate to core Engineering only when there’s a product-level gap • Capture and share knowledge • Write playbooks, scripts, and internal guides • Feed learnings back to Product and Engineering