Artificial Intelligence (AI) Architect

The Sr Engineer, Commercial AI Forward Deployment is an experienced engineer who embeds with the client's business customers and is the primary builder on a customer deployment or workstream. The role supports the client's commercial AI programs. Responsibilities include supporting its edge AI offering and the broader Physical AI program, but are not limited to them, and will extend to AI applications the client sells to business customers. Senior FDEs take a solution from the catalog, or a new design from the architect, and make it work in the customer's world: integrating devices such as cameras, sensors, drones, AMRs, and autonomous vehicles; building the sensor and vision data pipelines, fine-tuning, and inference services behind them; integrating ISV software; and deploying all of it over the client's network and edge. Physical AI work combines hardware, software, cellular networking, and AI in a single deployment, so the role calls for depth in at least one of these areas and working range across the others. The Sr Engineer writes and ships production code, reviews the code of Engineers on the engagement, and operates with significantly more autonomy than an Engineer. Success is measured by working deployments delivered into customer environments, time from kickoff to a working deployment, production stability after go-live, and the reusable components each engagement leaves behind.

Job Responsibilities

• Own the technical build for a customer deployment or workstream, from scoping the customer-specific changes through deployment, testing, and handoff to steady state.
• Write and ship production code for device integrations, sensor and vision data pipelines, model fine-tuning and evaluation, inference services, and ISV integrations on Telecommunication's edge platform.
• Lead technical discovery for the workstream with customer engineering teams, turning requirements into implementation plans with clear targets for latency, accuracy, and reliability.
• Integrate solutions with Telecommunication's network and edge infrastructure, working with Network RAN and Core engineering on connectivity, network slicing, SIM/eSIM provisioning, and edge compute capacity.
• Run Day 0 to 2 deployment and operations for the workstream, including regression testing, observability, incident triage, and root cause analysis of field issues.
• Package customer-specific work into reusable blocks for the shared library, and give product owners specific, evidence-based feedback on platform gaps.
• Explain technical tradeoffs clearly to customer stakeholders and to Telecommunication business and marketing teams, and escalate risks such as hardware lead times, site access, or network readiness early.
• Mentor Engineers on the engagement through code review, pairing, and delivery standards.
• Also responsible for other duties/projects as assigned by business management as needed.

Education and Work Experience

• Bachelor's Degree and 4 years of related work experience OR a combination of education and experience deemed equivalent (Required)
• Acceptable areas of study include Computer Science, Computer Engineering, Electrical Engineering, Data Science, Telecom Engineering, Robotics, or a related field (Preferred)
• 4-7 years of professional engineering experience with hands-on work in at least one of: IoT or edge systems, data science and ML pipelines, or cellular network engineering (Preferred)
• Experience in solutions engineering, deployment engineering, or forward-deployed roles with direct external customer exposure (Preferred)
• Track record of taking proof-of-concept or pilot systems into production with external customers, including work alongside systems integrators or multi-vendor teams (Preferred)

Knowledge, Skills and Abilities

• Production Software Development in Python, plus one of C++, Go, TypeScript, or Java (Required)
• Containerized and Edge Deployment (Kubernetes / OpenShift), CI/CD, and Observability (Required)
• Data and ML Pipelines (ingestion, fusion, fine-tuning, inference) (Required)
• Customer-facing Technical Communication (Required)
• Field Troubleshooting and Root Cause Analysis (Required)
• IoT and Device Integration: cameras, sensors, drones, robotics, autonomous systems (Preferred)
• Cellular Network and Connectivity: 5G, network slicing, edge/MEC, SIM/eSIM provisioning (Preferred)
• Edge and Orchestration Platforms such as AWS Outposts, Vantiq, or Spectro Cloud (Preferred)
• Agentic AI and Multi-agent Orchestration (Preferred)

Licenses and Certifications

• Cloud certification (AWS / Azure / GCP) (Preferred)
• Kubernetes certification (CKA / CKAD) (Preferred)
• FAA Part 107 Remote Pilot Certificate, for drone-related programs (Preferred)