AI Transformation Engineer — Frontline Deployments

Arkham Technologies; Palo Alto (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Arkham Technologies in Palo Alto seeks a Forward Deployed Engineer to drive the AI transformation journey for clients. You will work hands-on across data science, AI architecture, and implementation, partnering closely with client stakeholders to deliver high-impact solutions.

Typically contributing to 1-4 implementations simultaneously, you will build production-ready ML and GenAI systems while collaborating with BI, Finance, Operations, and business teams to deliver measurable business value.

Qualifications

• 2-3 years of hands-on Data Science experience.
• Experience delivering ML systems into production.
• Some exposure to client-facing or stakeholder-intensive environments.
• Proficiency in Python and SQL.
• Experience with forecasting and time-series models.
• Experience with supervised and unsupervised ML.
• Familiarity with Generative AI and prompt engineering.
• Familiarity with AI agents and LLM-based workflows.
• Proficiency with Git and collaborative development workflows.
• Good understanding of statistical modeling and model evaluation.
• Strong communication and collaboration skills.

Responsibilities

• Build and deploy ML models including forecasting, optimization, clustering and anomaly detection.
• Develop Generative AI workflows.
• Implement AI Agents that automate analysis and operational decisions.
• Follow best practices for model monitoring, retraining and governance.
• Contribute to early AI use-case delivery and ROI for clients.
• Define data requirements and modeling strategies with the team.

Skills

Python

SQL

Forecasting

Time-series modeling

Supervised ML

Unsupervised ML

Generative AI

Prompt engineering

AI agents

LLM workflows

Model evaluation

Communication

Tools

Git

Job description

Arkham Technologies in Palo Alto seeks a Forward Deployed Engineer to drive the AI transformation journey for clients. You will work hands-on across data science, AI architecture, and implementation, partnering closely with client stakeholders to deliver high-impact solutions.

Typically contributing to 1-4 implementations simultaneously, you will build production-ready ML and GenAI systems while collaborating with BI, Finance, Operations, and business teams to deliver measurable business value.