Remote Senior AI/ML Architect: Distributed Platform Lead

OpenKrill; United States; Remote; USD 180,000 - 230,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive health benefits

401(k) with match

PTO + holidays

Education & training benefits

Job summary

Raft is seeking a Lead AI/ML Engineer for the [R]AIMS platform. You will shape architecture, drive critical epics, and lead by doing, while mentoring engineers and shaping technical direction across the team.

You will collaborate with AI/ML engineers on model integration and deployment, work across edge and cloud environments, and engage directly with government stakeholders to demonstrate capabilities with credibility.

Qualifications

• 6+ years of hands-on experience building and shipping production software systems across the full stack.
• Deep software engineering fundamentals with demonstrated ability to design, build, and evolve complex systems that perform reliably at scale.
• Exceptional technical communication skills; able to lead through influence across engineering, product, and leadership stakeholders without requiring direct authority.
• Proven experience designing and evolving distributed systems, including service decomposition, inter-service communication patterns, fault tolerance, and observability.
• Strong hands-on experience with Kubernetes and cloud-native platform architecture in production environments.
• Experience building data-intensive or AI-enabled production systems with real operational users and real performance constraints.
• Demonstrated technical leadership over large, cross-functional engineering initiatives with clear ownership and accountability for outcomes.
• Strong system design and architecture decision-making ability, with a track record of making the right call under incomplete information.
• Some experience or exposure to training, fine-tuning, or deploying machine learning models in production contexts.
• Ability to obtain Security+ certification within the first 90 days of employment.
• US citizenship required; ability to obtain and maintain a Top Secret/SCI clearance

Responsibilities

• Drive architectural decisions across the [R]AIMS platform, evaluating tradeoffs across performance, scalability, security, and maintainability and building alignment across engineering and product stakeholders.
• Lead major technical epics from conception through delivery, decomposing ambiguous problems into executable plans and keeping cross-functional teams moving with clarity and momentum.
• Simplify and rationalize distributed system architecture as the platform scales, reducing incidental complexity and improving operational reliability without sacrificing capability.
• Optimize platform performance across both edge and cloud deployment targets, identifying and resolving bottlenecks in data-intensive, latency-sensitive operational environments.
• Establish strong engineering foundations and reusable technical patterns that improve developer productivity and code quality across the team.
• Mentor engineers at multiple levels, conducting design reviews, providing substantive code feedback, and actively elevating technical execution across the platform.
• Partner with AI/ML engineers on model integration, inference optimization, and the operational deployment of agentic workflows within [R]AIMS.
• Engage directly with customers and program stakeholders at operationally demanding environments across the Department of Defense, representing Raft’s technical capabilities with credibility and clarity

Skills

Distributed systems

Kubernetes

Cloud-native

Technical leadership

Technical communication

Security+

AI/ML platforms

Tools

Kafka

Kafka Streams

Apache Flink

Job description

Raft is seeking a Lead AI/ML Engineer for the [R]AIMS platform. You will shape architecture, drive critical epics, and lead by doing, while mentoring engineers and shaping technical direction across the team.

You will collaborate with AI/ML engineers on model integration and deployment, work across edge and cloud environments, and engage directly with government stakeholders to demonstrate capabilities with credibility.