Senior AI / Software Engineer – Systems & Applied AI at Skilldlabs

Location: Remote (Global)
Engagement: Contract or fractional (flexible hours)
Duration: 2–3+ year platform rebuild initiative

Overview

We are seeking an exceptional Senior AI / Software Engineer to help rebuild and modernize the technology platform of a long-established investigative technology company undergoing a full re-platform. This role is not a traditional engineering position where requirements are fully defined and handed down for execution. The ideal candidate must be capable of owning ambiguous problems, designing scalable systems, and executing independently. You will work on advanced systems involving video processing, AI/ML pipelines, voice agents, and large-scale data processing, helping the team build and operate a modern architecture while the system is actively running.

This is a role for a highly experienced engineer who thrives in complex environments and can immediately contribute without extensive direction.

Responsibilities:

System Architecture & Engineering

• Design and implement scalable backend systems supporting AI and data processing workflows
• Architect solutions that operate reliably under large-scale workloads
• Evaluate and redesign legacy components during the platform rebuild
• Identify architectural risks before they reach production scale

Applied AI / ML Systems

• Develop and integrate machine learning pipelines used in real-world investigative workflows
• Work with technologies such as:
  • Computer vision
  • Video processing pipelines
  • AI agents and automation systems
• Improve latency and performance of AI-driven workflows

Data & Platform Engineering

• Design systems capable of processing extremely large video datasets
• Build scalable pipelines for ingesting, processing, and analyzing media data
• Optimize storage architectures (object stores vs relational systems)
• Ensure systems scale without architectural bottlenecks

Problem Solving & Technical Leadership

• Evaluate complex engineering challenges and propose optimal solutions
• Challenge flawed technical assumptions when necessary
• Collaborate with a small team of senior engineers and contractors
• Rapidly prototype and test ideas without heavy process overhead

Required Experience

Core Engineering

• 10–20+ years of professional software engineering experience
• Extensive experience designing distributed systems at scale
• Strong architecture and system design capability
• Ability to work across multiple programming languages

AI / Machine Learning

Hands-on experience with applied ML systems such as:

• Computer vision frameworks (e.g. YOLO)
• ML frameworks such as TensorFlow or similar
• Retrieval-Augmented Generation (RAG) pipelines
• Experience integrating AI systems into production applications
• Candidates must understand AI systems at the engineering level, not simply prompt engineering.

Cloud & Infrastructure

• Strong experience with AWS architecture
• Experience with services such as Bedrock or similar model platforms
• Designing large-scale data processing pipelines
• Managing performance, latency, and cost optimization

Languages / Technical Stack

Environment is polyglot, and the team values engineering ability over specific language preference. Languages currently in use include:

• C#
• Node.js
• Python
• Java
• C/C++

What Makes This Role Unique

• Strong software engineering fundamentals
• Deep understanding of AI/ML systems beyond prompt engineering
• Ability to design scalable systems and challenge bad architecture
• Comfort working in a polyglot, evolving architecture
• A mindset of problem ownership rather than requirement execution

The most successful candidate will: The right candidate can take a loosely defined problem and design the right technical solution from first principles.

Ideal Candidate Profile

• Be strong technically
• Think like a systems architect
• Be able to hit the ground running with minimal direction
• Identify edge cases and scaling issues early
• Avoid over-engineering while still designing robust solutions
• Have the confidence to challenge poor design decisions
• This role is not suitable for engineers who only execute defined requirements.

Work Environment

• Small engineering team
• Mix of contractors and fractional specialists
• Highly collaborative but low process / high ownership
• Long-term rebuild initiative (2–3+ years)

What Success Looks Like

Within the first 90 days, the successful candidate will:

• Quickly understand the existing architecture and systems
• Begin solving complex technical problems independently
• Contribute architectural improvements to the platform rebuild
• Design scalable solutions for high-volume AI and video processing workflows

What we offer

• Opportunity to work on cutting-edge products
• Fully remote team with async-first collaboration
• Payment in USD
• PTO, paid holidays, and family leave
• Paid learning and sponsored certifications
• Computer Sponsor Program
• A dynamic and collaborative work environment