IC3 - AI Engineer

We’re building an AI- first organization — and we’re looking for engineers who actually build , not just experiment . We’re hiring an AI Engineer to develop , integrate , and maintain AI- powered products across our ecosystem — from LLM- based customer experiences to internal copilots that transform how teams operate .

You’ll be part of a centralized AI Products Chapter , embedding into squads to bring real AI solutions into production .

• Build and deploy Generative AI solutions (LLMs, RAG, agents, copilots) under standard production practices.
• Implement scalable AI components and services within production systems.
• Work across the full software lifecycle: assist in prototyping, deploy models, and optimize performance.
• Integrate AI models with real-world systems, APIs, data platforms, and backend workflows.
• Implement evaluation frameworks, monitoring mechanisms, and feedback loops to track model performance.
• Partner with Product, Data, and Engineering squads to deliver impactful AI-driven features.

• Solid software engineering background (Python + modern backend stack).
• Hands-on experience building with LLMs, Generative AI, or NLP frameworks.
• Practical experience deploying ML/AI features into production environments.
• Familiarity with cloud services (AWS/GCP), API design, and data pipelines.
• A strong problem-solving, execution-oriented, and continuous-learning mindset.

• You won’t just build models you’ll ship real AI products into production.
• You’ll collaborate across multiple squads gain broad exposure and technical growth.
• You’ll contribute directly to shaping best practices for AI Engineering within the organization.

• Experience: 3–5 years of overall experience in Data & Tech, with at least 1.5–2 years of hands‑on experience developing AI/ML and Generative AI solutions.
• Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or a related technical field.
• AI Competencies: Strong foundational understanding of Deep Learning, Natural Language Processing (NLP), and Generative AI (LLMs, RAG architecture, function calling, agents).
• Technical Stack: Proficiency in Python and familiarity with ML libraries (PyTorch or TensorFlow), alongside hands‑on use of AI frameworks (LangChain, LlamaIndex, or Hugging Face).
• Cloud & Data Platforms: Hands‑on experience with cloud‑native AI/ML services (AWS SageMaker or Google Vertex AI) and standard data processing tools.
• Infrastructure & Tools: Practical experience using vector databases (Pinecone, Milvus, Qdrant, or Weaviate) and MLOps tools for model tracking and logging.
• Communication: Ability to clearly explain technical trade‑offs and AI concepts to both technical teammates and product partners.
• Ethics & Compliance: Basic understanding of AI safety, data privacy, and responsible AI practices.
• Soft Skills: Proactive problem‑solving, strong sense of ownership, willingness to learn, and commitment to writing clean, maintainable code.