AI Engineering Lead

📋 Description

• Lead end-to-end project delivery with clear governance and strong stakeholder communication
• Mentor junior engineers and contribute to proposals and new business initiatives
• Define what AI systems should and should not attempt, and communicate risks and tradeoffs
• Design and build RAG systems, agentic frameworks, and LLM-powered solutions robust enough for
• Apply advanced prompt engineering techniques, including instruction design, few-shot sets
• Lead feasibility assessments to select the right approach among prompting, RAG, fine-tuning, or

🎯 Requirements

• Expert-level Python, strong Git practices, and experience with ML/LLM versioning
• Solid cloud experience across AWS, Azure, or GCP (Azure preferred), plus containerization and
• Hands-on RAG experience covering chunking, embeddings, retrieval, reranking, and evaluation
• Proven MLOps/LLMOps track record using tools such as MLflow, Weights & Biases, or similar
• Practical evaluation design skills, including metrics, dataset curation, and structured
• Experience with event-driven architectures, APIs, and microservices

🎁 Benefits

• Learning Opportunities: Certifications in AWS, Databricks, Snowflake; access to AI learning paths
• Travel opportunities to attend industry conferences and meet clients
• Mentoring and Development: Career development plans and mentorship programs
• Celebrations & Support: Special day rewards, company-provided equipment
• Flexible working options; details vary by location