Note: The job is a remote job and is open to candidates in USA. Verity is looking for a Senior AI Solutions Engineer to revolutionize how their Client Executives and Client Success Managers work. In this role, you'll design, build, and deploy intelligent automations and LLM integrations to enhance productivity and insights for clients.
Responsibilities
- Architect and deploy LLM-powered agents and workflows using Model Context Protocol (MCP) to seamlessly connect AI models with core tools like Salesforce, Salesintel, HubSpot, Jira, and Confluence
- Build autonomous research and productivity tools that assist CEs and CSMs with deep client/prospect backgrounding, real-time market research, and automated data entry/syncing between Salesforce and Jira
- Collaborate with Verity's Product Data Engineering team to analyze product usage and customer data, translating it into strategic insights that help CSMs proactively identify churn risks and uncover expansion opportunities
- Design, build, and maintain production-grade analytics dashboards to track key performance indicators (KPIs) regarding platform performance, customer health, and operational efficiency
- Act as a technical consultant, occasionally interfacing directly with clients to understand their data environments, help them maximize the ROI of Verity's solutions, and drive overall value realization
Skills
- 5+ years in a highly technical, data-driven role (e.g., AI Solutions Engineer, Analytics Engineer, or Solutions Architect), including 2+ years deploying LLMs in production, orchestrating multi-tool agentic workflows, and using modern connection protocols
- Proven experience with enterprise clients: strong consultative, communication, and storytelling skills to present technical data to non-technical stakeholders, plus the ability to unpack business friction points and architect scalable technical solutions
- Advanced prompt engineering (fine-tuning retrieval strategies, managing context windows for production LLMs) and demonstrable experience designing, building, or configuring MCP servers to connect LLMs to external data sources and enterprise APIs
- Strong SQL (PostgreSQL, Presto) for querying, transforming, and statistically analyzing complex data, plus expert-level dashboard wireframing and design for clean, actionable executive reporting
- Deep familiarity with REST/GraphQL APIs, webhooks, and OAuth, and Python proficiency (Pandas, NumPy, FastAPI) for data manipulation, backend automation, and building/testing/deploying MCP servers
- Ability to turn raw product telemetry into strategic insight for CSMs, and comfort acting as translator between Data Engineering and commercial/success teams
- Experience working closely with, or embedding tools within, Customer Success, Sales Operations, or Revenue Operations ecosystems
- Familiarity with our broader tech stack, including: Claude Cowork, Claude Code, and Claude Skills, plus LLM frameworks such as LangChain/LlamaIndex; Apache Superset; Python with Scikit-learn, RStudio, and PyCharm/VS Code; AWS QuickSight and Microsoft Power BI; and Git, the AWS ecosystem (Lambda, S3, Athena), and Apache Airflow
Benefits
- 401k match program
- Medical/dental/vision health benefits
- Flexible vacation policy
- Variable bonus program
Company Overview
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