Overview In this role you will design, build, and deploy generative AI and ML solutions that address real business problems. You will work within Slalom's Data & AI capability to develop cutting-edge AI tools and collaborate with engineers, data scientists, and AI leaders. You'll apply LLM-based approaches (RAG, agents, prompt engineering, fine-tuning) and advance production-quality AI implementations with a strong emphasis on validation, observability, and governance. This role offers hands-on influence across client work and internal AI communities, with a clear impact on scalable AI solutions and customer outcomes. You'll thrive in a collaborative, growth-oriented environment that values practical
Compensation / Benefits- meaningful time off and paid holidays
- parential leave
- 401(k) with matching
- health, dental, & vision coverage
- adoption and fertility assistance
- well-being reimbursement
Responsibilities- Design, build, and deploy generative AI and ML solutions to solve business problems
- Develop LLM-powered applications using RAG, agents, prompt engineering, tool calling, workflow automation, and fine-tuning
- Apply ML and DL methods to create AI tools for real-world use cases
- Contribute to design, development, presentation, and delivery of traditional ML solutions (CV, NLP, recommendations)
- Stay updated on AI/ML fundamentals and trends to inform solution discussions
- Mentor and share knowledge to grow the AI/ML community within the organization
Key requirements- 3+ years in production ML/model implementation
- 2-4 years in professional consulting (Managed or IT)
- Strong consultative and communication skills for diverse stakeholders
- Solid technical foundation with curiosity in ML/AI
- Fluency in AI/GenAI, ML, and at least one major cloud (AWS, GCP, Azure)
- Hands-on experience with generative AI: LLMs, embeddings, vector search, RAG, agents, prompt engineering, fine-tuning
- Experience with AI validation, observability, and production-grade metrics (accuracy, groundedness, safety, latency, cost, drift)
- Experience deploying ML/AI into production and discussing best practices and pitfalls
- Understanding of AI/ML validation frameworks and production-ready offerings
- Excellent Python skills for ML/AI use cases
- Data Science and/or Data Engineering background preferred
- strong communication
- collaborative mindset
- curiosity and continuous learning
- Generative AI / LLMs
- RAG, embeddings, vector search
- prompt engineering, fine-tuning
