Company Description Pixelvyne.ai builds Autonomous Enterprise Studios—AI solutions designed around full business functions rather than isolated tasks. Each Studio combines AI agents, data flows, exception rules, and accountability to deliver outcomes that matter inside an organization’s existing systems. Teams remain in control by defining what the Studio handles, how human oversight works, and how success is measured, with clear boundaries and exception routing. Forward-deployed engineers integrate Studios with current tools and processes, then expand their scope as performance proves value. Organizations can start with a single Studio and scale across HR, Finance & Procurement, Customer Service, IT, Facilities, Sales & Marketing, and Legal & Compliance to create a connected “Vyne” of automated functions. Qualifications
- Strong foundations in Computer Science and Software Development, including data structures, algorithms, and software engineering best practices.
- 5+ years of Hands-on experience building production-grade LLM applications and AI agents using open-source frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGen.
- Practical experience designing multi-agent workflows, including orchestration, state management, memory, tool calling, and human-in-the-loop controls.
- Experience with RAG pipelines, embeddings, and vector databases (e.g., FAISS, Chroma, Qdrant, Milvus, or pgvector).
- Experience working with open-source LLMs (e.g., Llama, Mistral, Qwen) and model serving tools such as vLLM or Ollama.
- Hands-on experience with Pattern Recognition and Neural Networks for building and optimizing ML/AI models.
- Practical knowledge of Natural Language Processing (NLP)



for designing and integrating language-based AI features.
- Proficiency with modern ML/AI frameworks and tools (e.g., Python, PyTorch, TensorFlow, Hugging Face Transformers, and model serving platforms).
- Experience deploying AI systems into production, integrating with APIs and enterprise applications, and working with cloud or containerized environments (e.g., Docker, Kubernetes).
- **Experience evaluating and monitoring LLM applications for quality, latency, and cost, using tools such as LangSmith or Langfuse.
- Ability to collaborate with cross-functional teams, translate business requirements into technical solutions, and communicate clearly with both technical and non-technical stakeholders.
- Bachelor’s or higher degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Background in applied ML/AI within enterprise settings, MLOps, or scalable system design is an advantage. Role Description This is a full-time, in office AI Engineer role based in Noida. The AI Engineer will design, develop, and deploy AI components and agents that power Pixelvyne.ai Studios across multiple business functions. Day-to-day responsibilities include building and training models, implementing pattern recognition and neural network architectures, and integrating NLP capabilities into enterprise workflows. The role involves collaborating closely with forward-deployed engineers and stakeholders to connect AI solutions with existing systems, refine data pipelines, and ensure robust performance in production environments. The AI Engineer will also monitor live systems, troubleshoot issues, optimize models, and contribute to continual improvements in reliability, scalability, and security.

📌 AI Engineering Lead (Noida)
🏢 Pixelvyne.ai
📍 Noida