Senior AI Data Engineer
About The Position
Accertify enables commerce by doing one thing extraordinarily well: pinpointing fraud. The company's Predictive Yes Platform helps businesses say yes to more - more good customers, more revenue, and more growth - without getting burned. It's a precise, confident, data-backed yes, made possible by joining signals across the entire customer lifecycle through unmatched data volume, layered AI-powered models, and a consortium approach that protects clients from bad actors spotted anywhere in the network while unlocking business with good actors verified anywhere in the network. With more than 10 billion transactions and over $1 trillion in commerce processed in 2025 alone, Accertify delivers the intelligence and precision that fraud and payments teams need to say yes confidently and enable growth. That's the More Yes difference. We are seeking an experienced Senior AI Engineer to lead the design, development, and deployment of intelligent systems that drive business impact. You will own end-to-end AI solutions, set technical direction, and mentor other engineers, working across machine learning, LLMs, retrieval systems, agentic workflows, and the data layers that feed them. This role requires deep technical expertise and a track record of shipping production AI systems at scale.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience).
- 5+ years of production software experience.
- Strong proficiency with AI/ML frameworks (OpenAI SDK, Hugging Face transformers, agentic orchestration frameworks).
- Strong Python AND strong SQL, both are first-class requirements. Comfortable with query optimization, indexing strategy, and data modeling.
- Demonstrated experience designing and operating medallion architectures (bronze/silver/gold) at scale.
- Experience handling data at scale, partitioning, batch pipeline design, query performance, and schema evolution.
- Production LLM experience, prompt engineering, retrieval (RAG), agentic orchestration, fine-tuning trade-offs.
- Experience with vector databases (pgvector, Pinecone, Weaviate, etc.) and production RAG patterns.
- Experience with AI observability and evaluation frameworks, OpenTelemetry, Phoenix or equivalent, golden-set eval, and judge-based eval methodology.
- Strong understanding of secure system design, authentication, API integrations, and PII-sensitive data handling.
- Track record of mentoring engineers and shipping cross-team initiatives.
- Strong problem-solving skills and ability to explain technical solutions to non-technical audiences.
Nice To Haves
- Hands-on experience with Model Context Protocol (MCP), building tools, OAuth flows, or MCP server integrations.
- Experience leading data engineering or data platform initiatives end-to-end.
- Experience with agentic AI frameworks (e.g., the OpenAI Agents SDK) in production.
- Experience deploying production systems across both cloud (AWS, GCP, Azure) and on-prem environments.
- Experience in fraud detection, financial services, or other PII-sensitive domains.
- Knowledge of MLOps tools and CI/CD for AI.
- Open-source contributions, conference talks, or technical writing in the AI/ML space.
Responsibilities
- Architect AI systems end-to-end. Set technical direction. Review and mentor others’ designs.
- Define how we use LLMs, routing, agentic orchestration, prompt patterns, fine-tune vs. prompt trade-offs, and model selection.
- Own deployment patterns across on-prem and cloud (Kubernetes, container infrastructure, secure integration). Drive operational excellence.
- Consult on the data layer, medallion design (bronze/silver/gold), RAG retrieval stores, schema evolution, drift detection, and query performance at scale.
- Define how we measure AI quality, use golden datasets, conduct judge-based eval, enable production observability (OpenTelemetry, Phoenix, or similar), and perform behavior testing.
- Mentor AI Engineers, lead code and design reviews, set engineering standards for the AI team, and drive cross-team initiatives with Data Science and Data Engineering teams.
- Set the bar for handling sensitive customer data, secure system design, authentication, PII safety, and compliance-aware patterns.
- Partner with product managers, data scientists, engineers, and stakeholders to align AI solutions with business needs.
Benefits
- Medical, dental, and vision coverage for you and your family.
- Paid time off, holidays, and personal days to maintain work-life balance.
- Competitive compensation, performance-based rewards, and local retirement or savings plans where applicable, along with financial education resources.
- Training programs, mentorship opportunities, and growth potential within the company.
- Mental health resources, fitness perks, and wellness programs.
- Commuter benefits, employee discounts, and company-sponsored events.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Associate degree
