Senior AI Engineer – Applied AI, ML Systems

Mitek Systems

AI Engineer developing AI solutions for digital identity authentication leader Mitek with a focus on ML systems. Collaborating with engineering and business stakeholders on AI use cases and production practices.

Posted 6/23/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $160,000 - $205,000 per yearWebsite

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design, build, and deploy AI solutions powered by ML, LLMs, and agentic AI systems that solve real 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 (RAG), context engineering, and multi-step agentic workflows.
Partner closely with product, engineering, data, and business stakeholders to prioritize AI use cases and align on success metrics, operational requirements, and delivery timelines.
Apply strong production practices across AI systems, including experimentation, versioning, observability, alerting and continuous improvement in production
Monitor, troubleshoot, and improve production AI systems by balancing quality, latency, cost, reliability, and maintainability.

Requirements

What you’ll need

Bachelor's degree in Computer Science or a related field, and knowledge, skills, and abilities typically associated with 6+ years of relevant experience, including:
4+ years of experience in one or more of the following areas:
- Machine Learning or Applied Modeling
- Data Engineering
- Software Engineering for Data-Intensive Systems.
2+ years of experience building LLM-based applications, including at least 1 year building agentic AI systems as part of that experience.
Experience building and operating production data pipelines, data platforms, or large-scale data-intensive systems.
Hands-on experience building LLM-powered applications, including context engineering, retrieval-augmented generation (RAG), evaluation frameworks, prompt engineering and optimization. Experience with model fine-tuning is preferred but not required.
Experience designing and implementing agentic AI systems, including multi-step workflows that incorporate planning, memory, handoffs, tool orchestration, and human-in-the-loop review.
Strong track record of defining evaluation strategies upfront and operating AI systems in production, including deployment, monitoring, observability, versioning, experimentation, and continuous improvement.
Advanced Python skills and experience taking AI solutions from prototype to production while balancing quality, latency, cost, reliability, and maintainability.

Benefits

Comp & perks

Wellness: Universal, supplemental, and private healthcare plan choices based on country specifics
Financial future: retirement/pension plan contributions, MTK stock plan participation
Income protection: life event & disability coverage
Paid time off: generous annual leave, company holidays, volunteer time off
Learning: e-learning license, tuition reimbursement, hackathons
Home office setup allowance
Additional/optional benefits: pet insurance, identity theft protection, legal assistance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Machine LearningApplied ModelingData EngineeringSoftware EngineeringLLM-based applicationsAgentic AI systemsProduction data pipelinesContext engineeringRetrieval-augmented generationPython

Soft Skills

CollaborationPrioritizationCommunicationProblem-solvingEvaluation strategy definitionMonitoringTroubleshootingContinuous improvementOperational alignmentQuality balancing

Certifications

Bachelor's degree in Computer Science