What You’ll Do
Responsibilities
- 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.
- Propose, design and own features from concept through delivery, including customer discovery, technical design, implementation, manual validation, release, bug resolution, and iteration.
- Work directly and build relationships 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.
- 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- building and contributing to internal tools and processes within and outside of our team.
What We’re Looking For
- 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.
- 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.You want to develop ideas independently to improve customer outcomes and team operations.
- 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.
- 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.
- 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.
Technical Areas You May Work In Already
- Extremely familiar with agentic coding (Cursor, Claude Code, Codex etc.)
- TypeScript / Node.js backend services
- ITOps domain expertise: change risk, ITSM, and incident prevention use cases
- React / Next.js customer-facing applications
- Slack and Microsoft Teams applications
- Agent workflow engines, Agent-tracing, Langsmith etc.
- RAG pipelines, vector databases, embeddings, and retrieval systems
- Knowledge graphs, agent memory, 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
You’ll Thrive Here If
This May Not Be the Right Role If
Why This Role Matters
- 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
- 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, or knowledge systems
- 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
- Ability to architect and build agent systems that retrieve context, call tools, execute actions, handle errors, and operate safely in enterprise environments
- Ability to learn quickly, work independently, and make forward progress in ambiguous situations
- Strong ownership of outcomes, customer impact, reliability, and follow-through
- Ability to ship and iterate quickly while maintaining sound engineering judgment
- Comfort with direct customer interaction and using customer feedback to shape priorities
- Product judgment focused on meaningful customer value
- Ability to challenge ideas directly while remaining collaborative and low-ego
- Excitement about applying AI to enterprise IT Operations problems
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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