Senior AI Engineer

Mitek Systems

AI Engineer with strong machine learning background at Mitek developing AI systems addressing business problems. Building reliable AI systems using ML, LLMs, and agentic AI systems.

Posted 4/28/2026full-timeRemote • California • 🇺🇸 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 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.

Requirements

What you’ll need

Bachelors’ degree in Computer Science or related field, and knowledge, skills and abilities typically associated with 6+ years of total relevant experience across ML and modern AI systems including:
4+ years of hands-on experience in machine learning
2+ years building LLM-based applications, 1 of which consists of building agentic AI systems as part of that LLM application experience
Expertise in ML, applied modeling, or NLP, including model development, evaluation, experimentation, and error analysis
Hands-on experience building LLM-based applications, including context engineering, retrieval, evaluation frameworks, and model fine-tuning.
Experience designing and implementing agentic AI systems, including multi-step workflows that use planning, memory, handoffs, tool orchestration, and human-in-the-loop review.
Strong experience with MLOps for ML systems, including model lifecycle management, deployment, monitoring, retraining, and production success metrics.
Strong experience with LLMOps for LLM-based applications, including prompt and workflow versioning, retrieval and response evaluation, observability, guardrails, and continuous improvement in production.
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

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningLLM-based applicationsagentic AI systemsapplied modelingnatural language processingmodel developmenterror analysisMLOpsLLMOpsPython

Soft Skills

collaborationprioritizationcommunicationproblem-solvingorganizational skills

Certifications

Bachelor's degree in Computer Science