Sr. Software Engineer II - AI Engineering (Remote Eligible)
About this role
Smartsheet needs a senior engineer to address the complexities of architecting, building, and operationalizing production-grade AI agents that scale reliably for enterprise users. Operating within the SmartAssist platform, the chosen candidate will bridge the gap between core engineering teams and AI platforms to help mature the agent development lifecycle. Responsibilities include designing robust retrieval-augmented generation pipelines, optimizing prompt patterns, and ensuring that automated systems deliver measurable accuracy in everyday business execution.
Working closely with product and cross-functional groups, the person in this position will shape system architecture while establishing rigorous development standards for responsible AI use. Ideal candidates bring extensive software engineering backgrounds paired with direct, hands-on experience deploying language models in production environments. Someone who thrives on clarifying ambiguous failure modes, mentoring peers, and driving technical standards forward will find a strong fit within this team.
What you will do
- Design and build production-grade LLM-powered agents and workflows, including making system architecture decisions and handling deployment strategies.
- Develop and optimize prompts, RAG pipelines, and agent reasoning patterns while building evaluation frameworks to measure accuracy and performance.
- Implement and manage end-to-end AI systems on cloud infrastructure with a focus on monitoring, optimization, and incident response.
- Collaborate with engineering, product, and cross-functional teams to translate business requirements into technical AI solutions.
- Mentor other engineers on applied machine learning best practices, modern AI development patterns, and production considerations.
- Establish standards for AI development, model governance, and responsible artificial intelligence across the organization.
What you need
- Candidates must have eight or more years of software engineering experience, including at least two years working directly with large language models in production.
- Deep hands-on experience with prompt engineering, context engineering, and retrieval-augmented generation architectures is required.
- Experience building or extending LLM evaluation frameworks, designing scorers, and working with golden datasets is essential.
- Strong Python programming skills are necessary, along with comfort working in data-heavy environments like Databricks or Delta tables.
- Applicants must possess strong cross-functional communication abilities to explain complex quality findings to technical and non-technical stakeholders.
- Legally eligible to work in the United States on an ongoing basis.
Nice to have
- 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
Benefits
- Employer subsidized medical, vision, and dental coverage for full-time employees
- 401k match of 50% of contributions up to the first 6% of eligible pay
- Monthly stipend to support work and productivity
- Flexible Time Away program alongside sick time off and 12 paid holidays per year
- Company-sponsored life insurance, short-term, and long-term disability plans
- Up to 24 weeks of parental leave and a personal paid volunteer day
Skills and tech stack
Questions candidates ask
Can I work remotely for this role?
Yes, teleworking options are available from any registered location in the United States where Smartsheet operates.
What is the salary range for this position?
The US base salary pay range is between $175,000 and $245,000 USD, determined by factors such as professional level, educational experience, skills, and specific location.
What core technologies and tools will I use?
You will work primarily with Python, cloud infrastructure such as AWS, GCP, or Azure, and data environments like Databricks or Delta tables while building RAG pipelines and LLM agents.
Who will I be working with on a regular basis?
You will work closely with engineering and AI platform teams, embedded in a critical area while collaborating daily with product and cross-functional groups.