The Product team forms the crux of our powerful platforms and helps connect millions of customers worldwide with the brands that matter most to them. This team of innovative problem solvers develops and builds products that position Epsilon as a differentiator, encouraging an open and balanced marketplace built on respect for individuals, where every brand interaction holds value. Our full-cycle product engineering and data teams chart the future and set new benchmarks for our products, by using industry standard methodologies and sophisticated capabilities in data, machine learning, and artificial intelligence. Driven by a passion for delivering smart end-to-end solutions, this team plays a key role in Epsilon's success story.
The Director Software Engineering is a transformative leadership role responsible for defining and driving the company's AI strategy, research agenda, and product integration roadmap. Reporting to the VP of engineering, this executive will build and lead a high-performing team of AI researchers, ML engineers, and data scientists to develop innovative AI capabilities that power our core products and create sustainable competitive advantage.
This leader will be the internal AI authority, advising the C-suite on emerging AI trends, responsible AI governance, and investment priorities. They will foster a culture of rapid experimentation while ensuring production-grade reliability, safety, and fairness across all AI systems.
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Responsibilities
Strategic Leadership
- Define and champion the company's multi-year AI vision, strategy, and investment roadmap in alignment with overall business objectives
- Advise the C-suite and Directors on AI trends, opportunities, and risk management strategies
- Build and scale a world-class AI organization, including recruiting, retaining, and developing top-tier AI talent
- Establish strategic partnerships with leading AI research institutions, cloud providers, and technology partners
Research & Development
- Oversee the full lifecycle of AI model development: research, experimentation, training, evaluation, deployment, and monitoring
- Drive applied research initiatives in areas including large language models (LLMs), computer vision, multimodal AI, and agentic systems
- Establish rigorous ML infrastructure standards covering model versioning, evaluation frameworks, and production deployment pipelines
- Lead innovation in generative AI, predictive analytics, and intelligent automation to unlock new product capabilities
Cross-Functional Collaboration
- Partner with Product, Engineering, Design, Legal, and Compliance teams to embed AI capabilities into the product portfolio
- Translate complex AI capabilities into tangible business value, working closely with Sales, Marketing, and Customer Success
- Collaborate with Data Engineering and Platform teams to build scalable, production-ready AI infrastructure
Responsible AI & Governance
- Champion responsible AI principles including fairness, transparency, safety, privacy, and explainability
- Develop and enforce AI ethics guidelines, bias mitigation frameworks, and model governance policies
- Ensure compliance with evolving AI regulations and industry standards across all jurisdictions of operation
Business Impact
- Own and report on AI program KPIs including model performance, business impact metrics, and team productivity
- Manage department P&L including headcount planning, compute costs, vendor contracts, and R&D budget allocation
- Identify and evaluate build/buy/partner decisions for AI capabilities and tooling
Qualifications
REQUIRED QUALIFICATIONS:
- 15+ years of experience in AI/ML, data science, or related technology fields
- 7+ years of progressive leadership experience managing large, multidisciplinary technical teams (50+ people)
- Proven track record of shipping enterprise-scale AI products or platforms that created measurable business value
- Deep technical expertise in machine learning, deep learning, NLP/LLMs, and modern AI frameworks (PyTorch, TensorFlow, JAX)
- Experience with cloud-scale ML infrastructure (AWS SageMaker, Google Vertex AI, Azure ML, or equivalent)
- Demonstrated experience building and scaling AI teams, with a strong record of recruiting and retaining top AI talent
- Executive-level communication skills with the ability to translate complex AI concepts for non-technical partners
- MS or PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field (or equivalent industry experience)
PREFERRED QUALIFICATIONS:
- Masters with published research in machine learning, NLP, computer vision, or related AI fields
- Experience with generative AI, foundation models, and RLHF/RLAIF training methodologies
- Background in responsible AI, AI safety, and model governance at scale
- Prior experience at a top-tier AI lab, research institution, or AI-first technology company
- Track record of successful strategic partnerships with academic institutions and AI ecosystem vendors
- Experience operating in regulated industries (healthcare, finance, or government)
