AI Engineering Manager

Position Overview

We are seeking a highly experienced, visionary, and Hands-on AI Engineering Manager to lead our AI engineering squad. In this role, you will bridge the gap between cutting-edge AI research and production-grade software engineering. With 1217 years of experience in the technology industry, you are someone who has evolved alongside the software landscapepossessing deep roots in backend engineering and distributed systems, coupled with advanced expertise in deploying Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems.As a hands-on manager, you will split your time between strategic technical leadership (coding, system architecture, prototyping) and people management (mentoring engineers, aligning with product strategy, and managing deliverables). You will be instrumental in defining our AI roadmap, building robust AI/LLM infrastructure, and delivering secure, scalable, and highly performant AI-driven applications.

Key Responsibilities

Technical Leadership & Architecture (approx. 50%)

• Architect AI Solutions: Design and implement robust, scalable, and secure architectures for AI-powered applications, prioritizing cost-efficiency, low latency, and reliability.
• Hands-on Coding: Write clean, production-grade, and highly optimized code (primarily in Python, Go, or Java). Lead by example in code quality, unit testing, and continuous integration.
• LLM Orchestration & RAG: Architect sophisticated Retrieval-Augmented Generation (RAG) pipelines, multi-agent frameworks (e.g., LangGraph, CrewAI, AutoGen), and advanced prompt-engineering workflows.
• Evaluation & Observability: Implement comprehensive evaluation frameworks (e.g., Ragas, TruLens) and LLM observability/monitoring systems (e.g., LangSmith, Phoenix, Arize) to ensure AI response quality and mitigate hallucinations.

Required Skills & Qualifications

• Total Experience: 12–17 years of professional software engineering and system design experience, with a proven track record of shipping production-grade SaaS, enterprise, or consumer applications.
• AI/ML Focus: 2-3 years of dedicated experience building and deploying machine learning or AI models, with at least 2 years of hands-on experience working directly with Generative AI, LLMs, and RAG architectures.
• Leadership Experience: 3+ years of experience formally managing engineering teams, executing performance reviews, and steering technical roadmaps.
• Core Technical Stack:
• Expertise in Java/.Net/Python.
• Experience with LLM Frameworks: LangChain, LlamaIndex, or Haystack.
• Familiarity with deep learning frameworks (PyTorch, TensorFlow) and Hugging Face Transformers.
• Proficiency in modern database technologies, specifically Vector Databases (Pinecone, Qdrant, Milvus, Weaviate).
• Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a highly quantitative field (or equivalent practical experience).

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