- Build production-grade software across backend services, APIs, web applications, workflow systems, AI agents, enterprise integrations, and automation platforms.
- Architect and implement AI-native capabilities using LLMs, prompting, tool calling, agent orchestration, RAG, vector search, knowledge graphs, embeddings, and structured/unstructured enterprise data.
- Use AI coding platforms such as Cursor, Claude Code, and similar tools as a core part of your development workflow to increase speed, exploration, and delivery quality.
- Write high-quality prompts for development, debugging, product behavior, agent execution, data extraction, reasoning workflows, and customer-facing AI experiences.
- Own features from concept through delivery, including customer discovery, technical design, implementation, manual validation, release, bug resolution, and iteration.
- Work directly with customers, GTM, product, and other engineers to identify high-value problems and translate them into product capabilities.
- Make pragmatic tradeoffs between speed, quality, reliability, cost, latency, scalability, and customer impact.
- Move fast in ambiguous problem spaces without hiding behind process, excessive documentation, or prolonged design debates.
- Manually validate AI and product behavior with care, especially where automated tests and evals are insufficient for probabilistic systems.
- Respond rapidly and transparently to bugs, regressions, and customer-impacting issues.
- Collaborate through paired development, design discussion, code review, debugging, and direct technical debate.
- Help raise the team’s bar for velocity, technical judgment, ownership, and customer-focused execution.
- Strong software engineering fundamentals across backend, full-stack, distributed systems, APIs, or product engineering.
- Hands-on experience building AI-enabled product capabilities with LLMs, RAG, vector databases, embeddings, agents, workflow automation, knowledge systems, or related technologies.
- Strong practical prompting skills, including prompt iteration, context design, tool-use instructions, structured outputs, and failure-mode analysis.
- High proficiency with modern AI development tools such as Cursor, Claude Code, ChatGPT, or similar platforms; you should already be using AI to materially improve your engineering output.
- Ability to architect and build agent systems that can reason, retrieve context, call tools, execute actions, handle errors, and operate safely in enterprise environments.
- High agency: you learn what you need to learn quickly, make forward progress independently, and do not wait for someone else to define every step.
- Extreme ownership: you care about outcomes, customer impact, reliability, and follow-through, not just completing assigned tickets.
- High velocity: you are motivated to ship, learn, and iterate quickly while maintaining sound engineering judgment.
- Customer curiosity: you want direct exposure to users and are comfortable using customer feedback to shape priorities.
- Product judgment: you can distinguish between what is technically interesting and what creates meaningful customer value.
- Healthy conflict: you can challenge weak ideas directly while remaining considerate, collaborative, and low-ego.
- Comfort with uncertainty, changing priorities, incomplete requirements, and fast iteration cycles.
- Excitement about applying AI to real enterprise IT Operations problems, not just building demos.
- TypeScript / Node.js backend services
- Fastify or similar API frameworks
- React / Next.js customer-facing applications
- Slack and Microsoft Teams applications
- Agent workflow engines and action execution systems
- RAG pipelines, vector databases, embeddings, and retrieval systems
- Knowledge graphs and enterprise knowledge modeling
- Prompt engineering, context engineering, and tool-use design
- ServiceNow, ITSM, monitoring, alerting, and incident management integrations
- Data ingestion, indexing, synchronization, and unstructured data processing
- S3, SQS, Lambda, and AWS-based service architecture
- Authentication, authorization, OAuth, SSO, API keys, and RBAC
- Incident response, change risk, and incident prevention use cases (domain knowledge/awareness)
- Competitive equity
- Remote-first environment
- Unlimited PTO
- Twelve (12) paid holidays throughout the year
- Comprehensive health benefits
- #PandaParent support. Financial assistance for fertility, adoption, and surrogacy expenses, plus up to eighteen (18) weeks of fully paid leave for birthing parents and up to twelve (12) weeks for non-birthing parents.
- Financial planning services
- Employee learning & development budget
- Values-based recognition (quarterly and annually)
- Social community & ERG programs
- Dog friendly office
- Lunches provided in office
- Flexible work environment along with a work-from-home stipend to support remote work arrangements
- Values-based culture
Skills Required
- Hands-on experience in building AI-enabled product capabilities
- Strong software engineering fundamentals across various systems
- High proficiency with modern AI development tools
- Ability to architect and build agent systems
- Extreme ownership and high urgency in problem-solving
- Excellent customer-facing skills and product judgment
What We Do
BigPanda is the only Event Correlation and Automation platform built for domain-agnostic AIOps. We transform how IT teams prevent outages and resolve incidents by turning data into insights and action. Without BigPanda, IT Ops and DevOps teams struggle with manual and reactive incident response capabilities that are badly suited for the scale, complexity and velocity of modern IT environments. This results in painful outages, unhappy customers, growing IT headcount and the inability to focus on innovation. Fortune 500 enterprises such as Intel, Cisco, United, Nike, Marriott and Expedia rely on BigPanda to prevent outages, reduce costs, and give their teams time back for digital transformation. BigPanda helps organizations take a giant step towards Autonomous IT Operations by turning IT noise into insights and manual tasks into automated actions. BigPanda is backed by top-tier investors including Sequoia Capital, Mayfield, Battery Ventures, Greenfield Partners and Insight Partners. Visit www.bigpanda.io for more information.
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