Sr. AI Engineer
Mitek SystemsAbout the role
At Mitek, we believe that teams are more resilient, effective, and innovative when they benefit from a wide range of ideas, lived experiences, and perspectives. The strength of our organization is deeply rooted in the people who power it.We know that a workforce reflecting the richness of our communities and customers helps us better serve their needs. These lived experiences influence our decisions, shape our products, services, and help us grow with intention. When it comes to talent, our goal is clear: to discover exceptional individuals and to ensure they discover us. We prioritize drive, skill, experience, and ambition in everything we do for our clients.
We are Virtual 1st! Whether you choose to work remotely from your home office or in-person from one of Mitek’s offices, our practices, processes and tools are designed to enable your success. At Mitek, the Future of Work is about flexibility and preference wherever and whenever we are working.
Summary
We are looking for an AI Engineer with a strong machine learning (ML) background and hands-on experience building modern AI systems. This role is best suited for someone who started in ML, applied modeling, or NLP, and later expanded into large language models (LLMs) and agentic AI systems. We are looking for someone with an evaluation-first mindset who believes AI systems should be designed with clear success criteria, testing methods, and monitoring plans from the start.
The ideal candidate brings solid ML foundations, experience working with third-party and open-source LLMs, and practical experience building multi-step AI workflows for real business problems. This background helps ensure these solutions are accurate, reliable, scalable, and grounded in sound evaluation practices. Humility, accountability, and a growth mindset are must-haves for this role. The right candidate is comfortable admitting mistakes, learning from feedback, and adjusting quickly when evidence shows a better path.
Why This Role Matters
This role matters because we need more than someone who can build AI features. We need someone who can build AI systems in a thoughtful and reliable way. That means starting with a clear plan for how quality, risk, and business impact will be measured, and carrying that through design, launch, and ongoing improvement. This role will also help strengthen how we run AI in practice, with solid MLOps and LLMOps across ML, LLM, and agentic AI systems.
What You’ll Do (Essential Responsibilities):
- Design, build, and deploy AI solutions powered by ML, LLMs, and agentic AI systems that address clear business problems.
- Define evaluation strategies upfront for each use case, including task success metrics, offline and online evaluation plans, error analysis, and production monitoring requirements.
- Build and improve LLM-based systems using prompt engineering, retrieval-augmented generation, and multi-step workflows.
- Apply MLOps and LLMOps practices, including experimentation, versioning, observability, alerting, model and prompt evaluation, and continuous improvement in production.
- Partner closely with product, engineering, and business stakeholders to prioritize AI use cases and align on success metrics, operational needs, and delivery timelines.
Who You Are (Soft Skills & Attributes):
- You bring an evaluation-first mindset and believe AI systems should not be designed or implemented without a
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