Note: The job is a remote job and is open to candidates in USA. Mitek Systems is a global leader in digital and biometric identity authentication, fraud prevention, and mobile deposit solutions. They are seeking a Senior AI Engineer with a strong foundation in machine learning and data engineering, responsible for designing and deploying AI solutions that address real business challenges.
Responsibilities
- 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
Skills
- 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
- Experience with vector databases, graph databases, retrieval quality tuning, and domain-specific optimization for LLM-based systems
- Experience designing reusable AI platforms, shared services, internal tooling, or infrastructure that improves AI development speed, consistency, and reuse
- Experience with cloud-native AI deployment, distributed systems, and scalable serving infrastructure for ML, LLM, and agentic AI applications
Benefits
- 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
Company Overview
Company H1B Sponsorship