Software Engineer, Applied AI Research

Hiring on behalf of our client

Title: Software Engineer, Applied AI Research

Time: Full-Time (US time zones)

Location: Remote (United States or Canada)

Compensation: $180,000 - $400,000/year USD + competitive equity

The Company

Our client is a B2B data and AI company helping businesses use customer data to deliver personalised experiences and improve marketing performance.

Its Composable Customer Data Platform enables companies to collect, prepare and activate customer data using their existing data warehouse. Its Agentic Marketing Platform and AI Decisioning products build on this foundation, helping marketers create campaigns and personalised customer interactions using customer data, brand context and performance insights. The team values customer impact, first-principles thinking, clear communication and compassionate collaboration.

Role Overview

Our client is seeking a Software Engineer, Applied AI Research to explore new techniques for agentic AI marketing applications, with a particular focus on image and video generation.

You will rapidly develop proofs of concept, experiment with generative AI methods and design evaluation systems to identify approaches that deliver meaningful customer value. The work centres on practical experimentation, prototyping and product applications.

The successful candidate will combine strong technical skills in backend architecture or probabilistic systems with quantitative thinking, creativity and product intuition. Candidates from software engineering, data science and machine learning backgrounds are welcome.

Key Responsibilities

• Develop and iterate on proofs of concept exploring how AI can improve data and marketing workflows.
• Experiment with generative AI approaches for image and video creation.
• Explore techniques to improve generated video quality, including the realism of generated people.
• Develop methods for generating brand assets that remain consistent with a company’s visual identity.
• Design evaluation and improvement systems that support autonomous iteration.
• Apply backend architecture or probabilistic systems expertise to design and implement solutions.
• Connect technical experiments to customer needs and potential product applications.
• Evaluate different approaches, communicate findings and use results to guide further development.

Requirements

• A formal university degree.
• Strong technical skills in backend architecture or probabilistic systems.
• Strong quantitative reasoning and probabilistic thinking.
• Product intuition and the ability to connect technical decisions to customer needs.
• Creativity, intellectual curiosity and an experimental approach to solving problems.
• Ability to understand and execute projects from initial problem definition through implementation and evaluation.
• Clear communication and a collaborative approach to working.
• Based in the United States or Canada and able to work US time zones.

The role targets approximately 2–12 years of relevant experience, with emphasis on demonstrated capability, impact, and potential for growth.

Prior professional experience with AI or LLMs is not required.

Nice to Have

• A Computer Science degree; study at a highly selective university is preferred.
• A background in data science or machine learning.
• Experience experimenting with LLM applications.
• Experience with model pre-training, post-training or fine-tuning.
• Experience with image or video generation.
• Familiarity with Python.

Working Arrangement

This is a full-time remote role for candidates based in the United States or Canada and working US time zones. Eligible visa transfers may be supported. Relocation assistance is not available.