Job
Description
Senior Applied AI Engineer : We are seeking a highly motivated Senior Applied AI Engineer to join our product team and spearhead the development of AI-driven features, with a particular focus on AI Agents. In this role, you will apply state-of-the-art AI methodologies including Large Language Models (LLMs) to solve complex problems and create innovative solutions across various product lines. If you are passionate about integrating cutting-edge AI into real-world applications, we would love to hear from you. Primary Skills: AI & Machine Learning: Proficiency in building AI Agents using frameworks like LangChain, CrewAI, or custom solutions. Strong understanding of Large Language Models (LLMs), including prompt engineering, ne-tuning, and retrieval augmented generation Familiarity with deep learning libraries such as PyTorch or TensorFlow Programming Languages: Python (preferred), Node.js, or Java for AI/ML and backend development DevOps & CI/CD: Git, Maven, Jenkins/GitHub Actions Cloud & Data: Google Cloud Platform (GCP) or Microsoft Azure for AI/ML workloads Frameworks: Django, Flask, FastAPI (Python) AI Development Acceleration: Experience with AI-driven development tools (e.g., GitHub Copilot, Cursor). Familiarity with vector databases (e.g., Pinecone, FAISS) and advanced search techniques Nice to Have : Experience with NLP, transformers, or advanced language modeling research Experience: Total Experience: 8+ years in software engineering or data science roles Relevant Backend Experience: 4+ years in machine learning or applied AI, with a proven track record of building and deploying AI/ML systems Key Responsibilities: Architect, build, and maintain AI Agents leveraging Large Language Models (LLMs) and advanced NLP techniques. Integrate AI Agents into various product areas, ensuring seamless user experiences and measurable business impact. Conduct proof-of-concepts (POCs) and research new AI methodologies, tools, and frameworks. Stay abreast of the latest advancements in LLMs, prompt engineering, and agent-based solutions. Collaborate with cross-functional teams (backend, DevOps, product) to productionize AI models and workows. Work with diverse data sources, setting up data pipelines and annotation workows as needed. Perform model training, hyperparameter tuning, and evaluation in collaboration with data engineers and data scientists. Troubleshoot and optimize AI pipelines, including inference latency, cost efficiency, and accuracy. Qualifications: Experience in a startup or fast-paced environment is a plus. Bachelors or Masters degree in Computer Science. Strong communication skills and ability to work in an agile development environment.
