Client-Facing AI & Data Engineer — Hybrid Role

Jobot; Atlanta (GA); Hybrid; USD 160,000 - 300,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) retirement plan

Paid time off and company holidays

Paid parental leave

Life and disability insurance

Professional development and training

Hybrid work flexibility

Performance-based bonus opportunities

Job summary

Jobot is seeking a Forward Deployed Engineer in the Atlanta area to partner with private equity portfolio companies. You will design and deliver data-driven software solutions, blending deep technical skills with exec-level communication to drive business outcomes.

Responsibilities include gathering requirements, leading workshops, articulating tradeoffs, and traveling to customer sites as needed to implement cloud-native data pipelines and AI-enabled workloads that solve real business problems.

Qualifications

• 5+ years of experience in Software Engineering, Data Engineering, ML Engineering, Solutions Engineering, or Forward Deployed Engineering.
• Demonstrated experience working directly with external customers, clients, or business stakeholders to define technical requirements and deliver software solutions.
• Experience leading customer discovery sessions, technical workshops, architecture discussions, or implementation engagements.

Responsibilities

• Bridge between external stakeholders and engineering teams; translate business needs into technical solutions.
• Lead conversations with executives, business leaders, and technical teams; manage expectations and communicate tradeoffs.
• Travel to customer sites as needed to support engagements and delivery of solutions.

Skills

Python

SQL

Customer-facing experience

Requirements gathering

Architecture discussions

Tools

AWS

GCP

Azure

Job description

Jobot is seeking a Forward Deployed Engineer in the Atlanta area to partner with private equity portfolio companies. You will design and deliver data-driven software solutions, blending deep technical skills with exec-level communication to drive business outcomes.

Responsibilities include gathering requirements, leading workshops, articulating tradeoffs, and traveling to customer sites as needed to implement cloud-native data pipelines and AI-enabled workloads that solve real business problems.