Senior Software Engineer II - Applied AI (Remote Eligible)

About the Role

The

AI Platform

Engineering team is looking for a highly motivated and talented engineer who is passionate about continuous learning and excited to grow in a fast-paced, innovative environment. We are an agile team that operates iteratively, focused on building high-quality software and adhering to rigorous operational best practices across complex, cross-functional distributed systems.
This full-time position reports to a Software Engineering Manager and can be located in our Bellevue, WA office, or you may work remotely from anywhere in the US where Smartsheet is a registered employer.
What Youll Do

Build the AI Platform Foundation : Lead the design and ownership of the core infrastructure that serves as the backbone for all Smartsheet AI experiences. Focus on building a robust, multi-tenant environment that reduces friction for internal teams, allowing them to deploy reliable and scalable AI features with ease.
Standardize the AI Developer Path : Architect high-level abstractions and "Golden Path" APIs that democratize AI development across Smartsheet. By insulating product teams from infrastructure complexity, you will enable them to ship intelligent features with high velocity while guaranteeing safety and consistency at scale.
Engineer AI Trust & Safety Systems : Establish the mission-critical monitoring and quality assurance layers that protect Smartsheet customers. By creating rigorous evaluation pipelines, you will ensure every AI-driven feature meets the high bar for safety, data privacy, and deterministic performance expected by our enterprise partners.
Drive technical strategy : Partner with principal engineers to define the technical roadmap for Smartsheet’s AI infrastructure, making architectural decisions that will shape how we build with AI for years to come.
What Were Looking For

Required
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
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
Strong Plus
Prior work in an Applied AI or LLMOps platform within a product company
Experience with the following:
Kubernetes (EKS/GKE):

The industry standard for AI. Skills include managing GPU scheduling, auto-scaling based on token throughput, and using tools like Karpenter for cost-efficient node provisioning.
Infrastructure as Code (IaC):

Using

Terraform, Pulumi, or AWS CDK

to provision Vector Databases, SQS queues, and S3 buckets.
Vector Databases:

Proficiency in managing and optimizing

Pinecone, Milvus, Weaviate, or Databricks Vector Search .
AI Gateways:

Building or configuring proxies (like

LiteLLM

or

Kong AI Gateway ) to handle rate-limiting, PII masking, and cost-tracking.
LLM Observability:

Setting up tracing tools like

Langfuse, LangSmith, or MLflow

to monitor "Time to First Token" (TTFT) and trace hallucination issues.
Model-Based Evals:

Implementing automated scoring systems (like

RAGAS

or

DeepEval ) that use an "LLM-as-a-Judge" to grade production outputs.
Benefits

Employer subsidized medical/vision and dental coverage for full-time employees
401k Match to help you save for your future (50% of your contribution up to the first 6% of your eligible pay)
Monthly stipend to support your work and productivity
US employees are automatically covered under Smartsheet-sponsored life insurance, short-term, and long-term disability plans
US employees receive 12 paid holidays per year
Up to 24 weeks of Parental Leave
Personal paid Volunteer Day to support our community
Opportunities for professional growth and development including access to Udemy online courses
Company Funded Perks, including a counseling membership, local retail discounts, and your own personal Smartsheet account
Teleworking options from any registered location in the U.S. (role specific)
Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.

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