Generative AI Engineer
About the job
- At least 2 years of professional experience in machine learning or artificial intelligence engineering, with expertise in large language model fine-tuning and deployment.
- Experience with LangSmith and LangChain for managing and optimizing large language model pipelines.
- Strong programming skills, particularly in Python, and experience with MLOps tools such as MLflow.
- A solid understanding of backend systems and software engineering best practices.
- Excellent communication skills and the ability to convey complex technical concepts to diverse audiences.
- Discover new ways to build agentic products that create autonomous AI employees.
- Architect orchestration layers for AI agents and their human counterparts to collaborate.
- Build feedback and learning mechanisms for agents across enterprise environments.
- Build systems that integrate AI models with third-party tools, enabling diverse real-world applications.
- Stay updated with advancements in large language models and machine learning to keep the company at the forefront of AI and agentic innovation.
- Prior startup or founding-team experience.
- Expertise with TensorFlow, PyTorch, or another machine learning framework.
- Familiarity with vector databases such as Pinecone and Weaviate, and MLOps tools such as MLflow and TFX.
- Experience with enterprise software such as Snowflake, Databricks, enterprise resource planning systems, customer relationship management systems, or reporting and analytics platforms.
- Experience with enterprise data engineering, including enterprise data pipelines and integrations.
About the company
Turgon AI is an AI-native system integrator that helps enterprises modernize IT and data infrastructure. It uses an agentic platform where specialized AI agents work with human experts to design, build, and continuously update data systems, enabling data migration, system consolidation and integration, data governance, and analytics acceleration. This human-in-the-loop approach bridges accuracy gaps and automates workflows, delivering faster project delivery and lower costs than traditional methods. The company differentiates itself with its AI agent pod and partnerships, such as the DynPro alliance, to tackle large-scale modernizations across industries like logistics, hospitality, finance, and retail.
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
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