AI Engineer

As an AI Engineer at Faktion, you work across the full spectrum of modern AI: from translating real customer challenges into concrete GenAI, Machine Learning and Computer Vision solutions, to engineering advanced AI systems where LLMs, agents, and classical models must reason, coordinate, and produce reliable outcomes under real-world constraints.

You are equally comfortable designing a multimodal ingestion pipeline that scales to 200,000+ pages, building agentic classification systems that enrich millions of data records, or developing computer vision models for industrial applications.

We are hiring a highly motivated AI Engineer to join our growing engineering team. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy AI-powered solutions that drive measurable impact for our customers across domains like finance, manufacturing, and operations.

Key Responsibilities

• Designing and implementing end-to-end AI solutions spanning GenAI, classical ML, computer vision, and agentic systems, tailored to the specific needs of enterprise customers.

• Translating ambiguous customer problems into concrete technical architectures, engaging directly with clients to define requirements and align on objectives.

• Developing and deploying production-ready AI backends using tools like Python, FastAPI, and Docker, with a strong focus on reliability and scalability.

• Building and maintaining evaluation pipelines, including LLM-as-a-Judge agents, to ensure continuous quality assurance from development through to production.

• Developing and maintaining MLOps pipelines, including data preprocessing, feature extraction, model training, and monitoring.

• Conducting research to stay current with the latest advancements in generative AI, machine learning, computer vision, and deep learning, and identifying opportunities to apply them for our customers.

• Collaborating with cross-functional teams to ensure AI solutions align with broader business goals and customer expectations.

• Developing clear and concise documentation, including technical specifications and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.

• Providing technical mentorship and guidance to junior team members.