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# Sr. Software Engineer II - AI Engineering (Remote Eligible)

- **Company:** Smartsheet Inc.
- **Location:** Bellevue, WA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $175,000.0 - $245,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Python (Programming Language), Software Engineering, Smartsheet, Large Language Models, Multi-Agent Systems, Prompt Engineering, Build Management, AI Platforms, Information Technology, Deployment Automation, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** September 2, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/phpvgo9sqg

## About the Role

* 8+ years of software engineering experience, with at least 2 years working directly with LLMs in production
 * Deep, hands-on experience with prompt engineering and context engineering, you understand how model behavior changes with framing, structure, and input design
 * Strong working knowledge of RAG architectures: chunking strategies, embedding models, retrieval evaluation, and failure diagnosis
 * Experience building or extending LLM evaluation frameworks, you have designed scorers, worked with golden datasets, and thought carefully about what good looks like
 * Fluency in agent system design, you don't need to own the architecture, but you can engage as a peer on architectural tradeoffs that affect quality
 * Strong Python skills; comfortable working in data-heavy environments (Databricks, Delta tables, or equivalent)
 * Ability to communicate complex quality findings (written and verbal) to both technical and non-technical stakeholders, you can explain what's broke, why it matters, and what needs to happen next without losing the room
 * Strong cross-functional judgment, you know when to escalate, when to resolve independently, and how to build credibility across engineering, product, and AI platform teams
 * A bias for clarity in ambiguous situations, when failure modes are murky and trade-offs are real, you bring structure and a clear point of view rather than waiting for consensus
 * Legally eligible to work in the U.S. on an ongoing basis
 * BS or MS in Computer Science, a related field, or equivalent industry experience

Strong Plus

 * Experience with MLflow or similar experiment tracking platforms
 * Familiarity with CI-integrated evaluation pipelines
 * Experience with multi-agent orchestration frameworks
 * Prior work in an Applied AI or LLMOps function within a product company

## Description

Smartsheet is building the next generation of AI-powered strategic planning and work execution agents through SmartAssist, our intelligent agent platform. You will work closely with Engineering and AI Platform teams, embedded in a team working in a critical area and building toward a mature Agent Development Lifecycle (ADLC).

You will architect how we design, build, and operationalize AI-driven solutions that transform work execution at enterprise scale.

You Will

 * Design and build production-grade LLM-powered agents and workflows within Smartsheet, including architecture decisions on system design, data pipelines, and deployment strategies
 * Develop and optimize prompts, RAG pipelines, and agent reasoning patterns; build evaluation frameworks to measure accuracy, hallucination rates, and performance across model versions
 * Implement and manage end-to-end AI systems on cloud infrastructure (AWS, GCP, or Azure), including monitoring, optimization, and incident response
 * Collaborate with Engineering, Product, and cross-functional teams to translate business requirements into technical AI solutions that drive real impact
 * Mentor and guide other engineers on applied ML best practices, modern AI development patterns, and production considerations
 * Establish best practices and standards for AI development, model governance, and responsible AI within the organization
 * Stay current with the rapidly evolving AI/LLM landscape and evaluate emerging tools, frameworks, and techniques for Smartsheet's needs
 * Contribute to a full stack application- both legacy and greenfield, * Delivered measurable, validated quality improvement on at least one SmartAssist agent across our defined quality dimensions
 * Expanded evaluation coverage to close the most significant blind spots in our current framework
 * Established a repeatable quality improvement methodology the broader team can apply