About Xerago
At Xerago, we’re a 20-year-old Marketing & Technology company blending data, creativity, and AI to drive measurable impact for global brands. Our AI Engineering group partners with Digital Engineering to build production-grade AI systems - accelerating innovation from idea to impact with GenAI, MLOps, and automation. If you love turning cutting-edge research into business-ready solutions at speed, this is your arena.
Responsibilities:
What You’ll Do Here
- Architect and design scalable, efficient AI systems and reference architectures for rapid iteration.
- Lead the Agile AI build path from DemoBytes → POC → MVP → Demoable → Production, ensuring clear stage gates and documentation.
- Drive a fast release cadence: monthly demo drops and production releases every two months.
- Integrate AI services and LLMs into existing platforms, data pipelines, and APIs with reliability and security in mind.
- Establish best practices for model evaluation, testing, observability, and CI/CD in MLOps.
- Mentor engineers on modern AI stacks, code quality, and experiment tracking.
- Champion ethical AI, privacy-by-design, and compliance in data handling and deployments.
- Track the AI landscape and propose pragmatic adoption of new models, tools, and methodologies.
Who We’d Love to Work With
We’d love it if you bring a mix of:
- 4+ years in AI/ML engineering/architecture with a strong record of rapid prototyping → production.
- Deep hands-on with Python and modern ML/DL frameworks: TensorFlow, PyTorch, Keras.
- Experience with LLMs and related tooling (prompting, RAG, fine-tuning, evaluation).
- Comfort with platforms/tools such as Hugging Face, scikit-learn, spaCy, NLTK, Gensim, YOLO, FastAI, and experiment tracking (Weights & Biases).
- Familiarity with WatsonX or similar enterprise AI platforms is a plus.
- Exposure to AI dev environments like Cursor, Windsurf, and AI coding copilots; familiarity with Claude or similar LLMs.
- Ability to translate complex AI concepts into practical designs for engineers, PMs, and business stakeholders.
- Strong communication, documentation, and collaboration chops.
- Bonus points if you’re familiar with MLOps stacks (Docker, Kubernetes, model registries), vector databases, retrieval pipelines, and evaluation frameworks.
What You Can Expect Here
- At Xerago, we believe in growth through innovation and teamwork.
- A collaborative culture that values curiosity, ownership, and open communication.
- Real runway to experiment with GenAI, automation, and predictive analytics—and ship to production.
- Clear impact, continuous learning, and mentors who care about your craft and career.
Work Location: In person
