Senior AI Engineer – Applied AI, ML Systems

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and implement AI solutions utilizing ML, LLMs, and agentic AI systems to address genuine business challenges.

• Establish evaluation strategies from the outset for each use case, encompassing task success metrics, offline and online evaluation plans, error analysis, and production monitoring requirements.

• Construct and enhance LLM-based systems employing prompt engineering, retrieval-augmented generation (RAG), context engineering, and multi-step agentic workflows.

• Collaborate closely with product, engineering, data, and business stakeholders to prioritize AI use cases and ensure alignment on success metrics, operational requirements, and delivery timelines.

• Implement robust production practices across AI systems, including experimentation, versioning, observability, alerting, and continuous improvement in production.

• Oversee, troubleshoot, and refine production AI systems by balancing quality, latency, cost, reliability, and maintainability.

⛳️ Requirements

• A Bachelor's degree in Computer Science or a related field, along with knowledge, skills, and abilities typically associated with 6+ years of relevant experience, which includes:

• 4+ years of experience in one or more of the following domains:

• - Machine Learning or Applied Modeling

• - Data Engineering

• - Software Engineering for Data-Intensive Systems.

• 2+ years of experience in developing LLM-based applications, with at least 1 year focused on building agentic AI systems during that time.

• Experience in constructing and managing production data pipelines, data platforms, or large-scale data-intensive systems.

• Hands-on experience in developing LLM-powered applications, including context engineering, retrieval-augmented generation (RAG), evaluation frameworks, and prompt engineering and optimization. Familiarity with model fine-tuning is preferred but not mandatory.

• Experience in designing and implementing agentic AI systems, involving multi-step workflows that integrate planning, memory, handoffs, tool orchestration, and human-in-the-loop review.

• Proven ability to define evaluation strategies from the beginning and manage AI systems in production, covering deployment, monitoring, observability, versioning, experimentation, and continuous improvement.

• Proficient in Python and experienced in taking AI solutions from prototype to production while maintaining a balance of quality, latency, cost, reliability, and maintainability.

🏝️ Benefits

• Wellness: Universal, supplemental, and private healthcare plan options tailored to country specifics.

• Financial future: Contributions to retirement/pension plans and participation in the MTK stock plan.

• Income protection: Coverage for life events and disability.

• Paid time off: Generous annual leave, company holidays, and volunteer time off.

• Learning: Access to e-learning licenses, tuition reimbursement, and participation in hackathons.

• Home office setup allowance.

• Additional/optional benefits: Pet insurance, identity theft protection, and legal assistance.