Forward Deployed Engineer

Arkham Technologies

$110K — $130K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 2-3 years of hands-on Data Science experience
  • Experience delivering ML systems into production
  • Exposure to client-facing or stakeholder-intensive environments
  • Solid proficiency in Python and SQL
  • Experience with forecasting and time-series models
  • Familiarity with Generative AI and prompt engineering
  • Proficiency with Git and collaborative development workflows

Responsibilities

  • Drive AI transformation for customers through hands-on work
  • Build and deploy robust ML models and GenAI workflows
  • Implement AI agents for automating analysis and decisions
  • Monitor, retrain, and govern AI models following best practices
  • Deliver operational AI solutions that address core business pain points within weeks
  • Collaborate on defining data requirements and modeling strategies

Benefits

  • Real ownership in driving transformation
  • Opportunity for substantial professional growth
  • Work with ambitious teams solving meaningful problems
  • Hands-on experience in implementing high-impact AI solutions
Full Job Description
Forward Deployed Engineer

About the Role

As a Forward Deployed Engineer, you help drive the AI transformation journey for our customers. You work hands-on across data science, AI architecture, and implementation, partnering closely with client stakeholders to deliver high-impact solutions.

Once a customer's Data Platform is live in Arkham, you help deliver and expand AI use cases. You partner with BI, Finance, Operations, and business stakeholders to:
  • Identify high-leverage AI opportunities
  • Build robust ML and GenAI solutions
  • Deploy production-ready systems
  • Support adoption across the client organization


You will typically contribute to 1-4 implementations simultaneously, working alongside senior team members.

What You'll Work On
  • Build and deploy ML models (like forecasting, optimization, clustering, and anomaly detection models)
  • Develop Generative AI workflows
  • Implement AI Agents that automate analysis and operational decisions
  • Follow best practices for model monitoring, retraining, and governance
  • Contribute to the first "Aha" moment: within 2-4 weeks, help deliver an operational AI solution that solves a core business pain point
  • Define data requirements and modeling strategies in collaboration with the team


What We Require
  • 2-3 years of hands-on Data Science experience
  • Experience delivering ML systems into production
  • Some exposure to client-facing or stakeholder-intensive environments
  • Solid 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


Why This Role Is Different

You don't just build models, you help drive transformation. You work directly with ambitious teams solving meaningful problems, with real ownership and room to grow.

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