Required AI Engineer
As an AI Engineer, you will:
Play a central role in advancing AI capabilities across the company and turning emerging AI technologies into practical, production-ready solutions
Research and evaluate new AI technologies, identify valuable use cases and develop solutions that improve internal workflows, existing products and enable new AI-powered capabilities
Lead AI solutions end to end, from research and proof of concept to design, development and production
Collaborate closely with development, product and business teams to integrate AI models, agents, data and reusable AI services into existing systems
Design and develop RAG, knowledge systems, AI agents and multi-agent workflows
Evaluate and benchmark AI models and solutions, balancing quality, accuracy, latency, throughput and cost
Find creative and practical solutions to complex technical and business challenges and help expand the companys internal AI ecosystem
Requirements: If you have:
At least 3 years of experience in software engineering, machine learning engineering, applied AI or a related technical role
Strong Python programming skills and experience building production-grade software, APIs and microservices
Hands-on experience developing AI-powered applications and taking them from proof of concept to production
Strong understanding of LLMs and transformer architectures
Experience with RAG, embeddings and vector databases
Experience in developing AI agents, tool-using workflows, MCP integrations or similar technologies
Experience in evaluating and benchmarking AI models and solutions
Familiarity with model-serving technologies such as vLLM, LiteLLM, SGLang, TGI or Triton
Working knowledge of Docker, Kubernetes, Helm, Linux, Git, CI/CD and GitOps
It would be great if you also have:
Experience with PyTorch, Hugging Face Transformers or similar frameworks
Experience with fine-tuning techniques such as LoRA, QLoRA, SFT, preference optimization or distillation
Experience with GraphRAG, knowledge graphs, code graphs or other graph-based AI systems
Experience optimizing model inference through quantization, batching, caching, parallelism or GPU-aware deployment
Experience with multimodal models, synthetic data generation or AI model evaluation
Experience delivering AI solutions in security-sensitive, regulated, on-premises or disconnected environments
B.Sc. in Computer Science or equivalent experience.
This position is open to all candidates.