Senior Software Engineer, AI Platform

BigPanda•Remote - USA,

13d•$187,000 - $220,000•Remote

About The Position

As a Senior Software Engineer on BigPanda’s AI Platform team, you will design, build, and ship platform capabilities that power AI across the company’s products. You will own meaningful features end to end: understand customer problems, shape solutions, make technical decisions, build and validate systems, launch them, respond to issues, and iterate quickly. The work spans data ingestion and synchronization, enterprise integrations, LLMs, agents, RAG, knowledge graphs, vector databases, workflow orchestration, automation, web applications, APIs, authentication and RBAC, and operational data pipelines. AI Platform is building shared infrastructure for BigPanda’s generative AI products for IT Operations, including unified data connectors, secure enterprise-data ingestion and indexing, unified identity and access, and agentic infrastructure for incident response, prevention, automation, knowledge retrieval, and operational intelligence. The team operates in an early-stage platform environment within an established enterprise company, prioritizing customer value, speed, pragmatic decisions, ownership, and action amid ambiguity. The role combines engineering execution with product ownership and customer collaboration. You will meet and build relationships with customers, develop ideas, help shape the strategic roadmap, and make technical choices that influence customer experience across the platform. You will also contribute to team practices, tools, and processes, and help raise the bar for engineering velocity, technical judgment, ownership, and customer-focused execution. BigPanda describes itself as a provider of agentic automation for IT operations, helping enterprise IT teams transform manual and reactive processes into intelligent systems that detect, respond to, and prevent incidents. The position is remote-based and open to candidates in the United States across Mountain, Central, and Eastern time zones. Visa sponsorship is not available. The anticipated base salary range is $187,000–$220,000; actual pay varies with experience, qualifications, skills, and location. The total rewards package includes base pay, bonus, equity, and benefits.

Requirements

Strong software engineering fundamentals in backend, full-stack, distributed systems, data pipelines, 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.
Ability to learn quickly, make independent progress, and develop ideas to improve customer outcomes and team operations.
Ownership of outcomes, customer impact, reliability, and follow-through.
Ability and motivation to ship, learn, and iterate quickly while maintaining sound engineering judgment.
Interest in direct user exposure and comfort using customer feedback to shape priorities.
Product judgment to distinguish technical interest from meaningful customer value.
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, and current use of AI to materially improve engineering output.
Ability to architect and build agent systems that retrieve context, call tools, execute actions, handle errors, and operate safely in enterprise environments.
Ability to challenge ideas directly while remaining considerate, collaborative, and low-ego.
Comfort with uncertainty, changing priorities, incomplete requirements, and fast iteration cycles.
Interest in applying AI to real enterprise IT Operations problems rather than only building demos.

Nice To Haves

Familiarity with agentic coding tools such as Cursor, Claude Code, or Codex.
Experience with data ingestion, indexing, synchronization, and unstructured data processing.
Experience with ServiceNow, Snowflake, ITSM, monitoring, alerting, or incident-management integrations.
Experience with RAG pipelines, vector databases, embeddings, and retrieval systems.
Experience with knowledge graphs, agent memory, or enterprise knowledge modeling.
Experience with authentication, authorization, OAuth, SSO, API keys, or RBAC.
Experience with TypeScript or Node.js backend services.
Experience with S3, SQS, Lambda, or AWS-based service architecture.
Experience with React or Next.js customer-facing applications.
Experience with agent workflow engines or agent tracing tools such as LangSmith.
Experience with prompt engineering, context engineering, or tool-use design.
IT Operations domain expertise, including change risk, ITSM, or incident-prevention use cases.

Responsibilities

Build production-grade software across backend services, APIs, data-ingestion pipelines, enterprise integrations, web applications, workflow systems, and automation platforms.
Build and own secure, reliable ingestion of customer data from enterprise systems such as ServiceNow and Snowflake.
Architect and implement AI-native capabilities using LLMs, prompting, tool calling, agent orchestration, RAG, vector search, knowledge graphs, embeddings, and structured or unstructured enterprise data.
Use AI coding platforms such as Cursor and Claude Code as part of the development workflow to improve speed, exploration, and delivery quality.
Write 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 with customers, go-to-market teams, product, and engineers to identify high-value problems and turn them into product capabilities.
Make pragmatic tradeoffs among speed, quality, reliability, cost, latency, scalability, and customer impact.
Make progress in ambiguous problem spaces without relying on excessive process, documentation, or prolonged design debates.
Respond rapidly and transparently to bugs, regressions, and customer-impacting issues.
Collaborate through paired development, design discussions, code review, debugging, and technical debate.
Contribute to internal tools and processes and help improve team velocity, technical judgment, ownership, and customer-focused execution.
Meet and build relationships with customers, develop product ideas, and contribute to the strategic roadmap and technical decisions.
Share best practices and identify opportunities to improve how the team operates.

Benefits

Competitive equity
Remote-first environment
Unlimited PTO
Twelve paid holidays throughout the year
Comprehensive health benefits
Financial assistance for fertility, adoption, and surrogacy expenses
Up to 18 weeks of fully paid leave for birthing parents and up to 12 weeks for non-birthing parents
Financial planning services
Employee learning and development budget
Values-based recognition, quarterly and annually
Social community and employee resource group programs
Dog-friendly office
Lunches provided in the office
Flexible work environment
Work-from-home stipend
Competitive cash compensation
Bonus
Career development and opportunities to develop skills