Forward Deployed Engineer
The posting does not state a salary. This range is our estimate from the role, the location and the stack — treat it as a guide, not an offer.
- Level
- Mid
- Apply from
- United States
About the role
- Drive AI transformation for clients
- Build and deploy ML models
- Collaborate with stakeholders for solutions
- Support adoption of AI systems
- Contribute to high-impact implementations
Skills the posting asks for
- Python
- SQL
- Machine Learning
- Generative AI
Summarised from the employer’s posting, which is reproduced in full below.
The employer’s full posting
Forward Deployed Engineer
About Arkham:
Arkham is a Data & AI platform that helps large enterprises:
- Unify fragmented systems and data
- Build a single source of trusted operational metrics
- Solve complex challenges with AI tailored to their operations
Teams at Circle K and Kimberly-Clark partner with us to deploy AI-powered solutions for sell-out forecasting, pricing and promo analysis, and automated order assignment. With Arkham, they achieve high-impact results fast, creating a strong foundation for long-term AI transformation.
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.