Overview
The Applied AI / GenAI Engineer builds intelligent features and products powered by large language models and generative AI. This role focuses on turning cutting edge research into reliable, high-impact applications that solve real user problems.
Your Role and Responsibilities
What You’ll Do
Key Responsibilities
- Design and build LLM-powered features: chat, summarization, search, extraction, and generation.
- Develop and optimize RAG pipelines, embeddings, and retrieval strategies.
- Fine-tune, evaluate, and benchmark models for quality, latency, and cost.
- Build robust evaluation and guardrail systems to ensure safe, accurate outputs.
- Collaborate with product to define AI-driven user experiences.
- Monitor production performance and continuously improve model behavior.
REQUIREMENTS
What This Role Requires
Education
- Bachelor’s degree in Computer Science, Machine Learning, or a related technical field.
Experience
- 3+ years in software engineering, with hands-on GenAI/LLM project experience.
- Experience shipping AI features to production.
Technical Skills
- Strong Python skills and familiarity with modern AI libraries.
Experience with LLM APIs (OpenAI, Anthropic, open-source models) and orchestration frameworks. - Knowledge of vector databases (Pinecone, Weaviate, pgvector) and embedding models.
- Understanding of prompt engineering, evaluation, and observability.
- Nice to have: fine-tuning, distillation, and model-serving experience.
Soft Skills
- Curiosity and passion for staying current with a fast-moving field.
- Pragmatic engineering judgment.
- Clear communication of technical trade-offs.
- Collaborative, product-minded approach.
Working at Motivus
What Working Here Looks Like
- Guild community: You’re part of the [Data & AI / Backend / Cloud] Guild — a community of practitioners in your domain. Structured learning, peer review, and certifications happen here, not in isolation.
- Outcome accountability: Your work connects directly to a client result. We don’t measure activity — we measure delivery.
- AI in your workflow: Through AI Champions and Guild initiatives, you’ll actively use and shape how AI tools are applied to engineering work — not just hear about it in a townhall.
- Defined career path: Structured progression from individual contributor to technical lead to Guild leadership, with certifications and milestones that are visible, not arbitrary.
