Staff AI/ML Platform Engineer - Remote (US)

Raft; Tampa (FL); Remote; USD 180,000 - 230,000; Full time

Benefits offered by this job

Highly competitive salary

Fully covered healthcare, dental, and

401(k) and company match

Take as you need PTO + 11 paid..

Education & training benefits

Generous Referral Bonuses

Job summary

Raft is seeking a Staff AI/ML Software Engineer to shape the [R]AIMS platform, drive architecture, and codify engineering patterns across a distributed production system. You will work hands-on while setting direction and collaborating with platform, product, and delivery teams.

Ideal candidates will have strong Kubernetes and cloud-native experience, plus experience with AI/ML production systems. This is a remote US-based role with some travel and top-security requirements.

Qualifications

• 6+ years of hands-on software development across frontend, backend, infra, and ML.
• Strong distributed systems design, fault tolerance, and observability.
• Citizenship and security clearance readiness: US citizenship and Top Secret/SCI eligible.

Responsibilities

• Lead architectural decisions across the [R]AIMS platform with cross-functional stakeholders.
• Drive major technical epics from conception to delivery with clear plans.
• Reduce complexity while scaling distributed systems and improving reliability.
• Collaborate with AI/ML teams on model integration and deployment.
• Mentor engineers and elevate engineering practices through reviews.
• Engage with customers and DoD stakeholders to communicate technical capability.

Skills

Full-stack development

Distributed systems

Kubernetes

Technical leadership

System design

AI/ML production systems

Tools

Kafka

Kafka Streams

Apache Flink

Job description

Raft is seeking a Staff AI/ML Software Engineer to shape the [R]AIMS platform, drive architecture, and codify engineering patterns across a distributed production system. You will work hands-on while setting direction and collaborating with platform, product, and delivery teams.

Ideal candidates will have strong Kubernetes and cloud-native experience, plus experience with AI/ML production systems. This is a remote US-based role with some travel and top-security requirements.