Forward Deployed Engineer
About the job
- At least 7 years of engineering or technical experience, with meaningful exposure to customer-facing or implementation work.
- Ability to code, understand how large-language-model-based systems work at a practical level, build agents, and apply basic data engineering skills.
- Ability to explain complex technical constraints to non-technical stakeholders and write precise bug reports for engineers.
- Experience working in data lakes, data warehouses such as Snowflake and Databricks, enterprise resource planning systems, and other similar systems of record.
- Ability to work with ambiguity and the pace of an early-stage startup, including context-switching between customer escalations, product scoping sessions, and sales calls.
- Own the last-mile execution of customer deployments by configuring, coding, customizing, and troubleshooting artificial intelligence solutions so they work reliably in customers' specific environments, data landscapes, and workflows.
- Serve as the human backstop when artificial intelligence agents require human judgment, review, or escalation.
- Identify patterns in human interventions and feed them back to product and engineering teams to reduce manual effort over time.
- Act as the voice of the customer inside Turgon by synthesizing customer pain points, edge cases, and feature requests into actionable briefs for product and engineering teams.
- Directly influence the product roadmap.
- Prior experience in a Forward Deployed Engineer or Solutions Engineer role at a business-to-business software-as-a-service or artificial intelligence company.
- Hands-on experience with large language model tooling, including LangChain, LangGraph, retrieval-augmented generation pipelines, and vector databases.
- Experience supporting or closing enterprise sales cycles in a technical capacity.
About the company
Turgon AI is an AI-native system integrator that helps large enterprises modernize their IT and data infrastructure. It combines proprietary AI agents with human experts to convert legacy, siloed systems into AI-ready data foundations. Its platform covers data migration, system consolidation and integration, data governance, and analytics enablement, working with enterprise systems such as Salesforce, Snowflake, Databricks, SAP, and Oracle. The company serves customers in logistics, supply chain, hospitality, finance, and retail, and highlights case studies like McCarthy Tire Service and Penguin Solutions. Turgon differentiates itself by integrating AI-powered agents with human expertise to perform data modernization end-to-end, rather than relying on traditional, purely human-driven system integration. Its goal is to help enterprises unlock value from their data by creating unified, governable data foundations that enable scalable analytics and AI initiatives.
Company Size
11-50
Company Stage
Seed
Total Funding
$6.5M
Headquarters
San Francisco, California
Founded
2024
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Simplify's Take
What believers are saying
- DynPro and Turgon announced 6-12 week modernization cycles in February 2026.
- Turgon reported 2025 backing from CIV, Founder Collective, and Slow Ventures.
- Hiring for sales, engineering, and delivery roles signals active customer demand and expansion.
What critics are saying
- Turgon AI remains a 2024 startup; one partnership and limited public traction prove little.
- DynPro can absorb the best parts of Turgon's workflow, commoditizing the startup by 2027.
- Enterprise modernization buyers distrust autonomous agents after a failed migration can destroy a career.
What makes Turgon AI unique
- Turgon AI pitches AI-native system integration, pairing agents with human experts.
- Its February 2026 DynPro partnership adds implementation depth and enterprise credibility.
- San Francisco and Delhi operations support 24-hour delivery across modernization projects.
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Benefits
- Company Equity
- Hybrid Work Options