Vacancy description
Axtria - Ingenious Insights
India, Noida
Axtria - Generative AI Architect - LLM/RAG in Noida, India is listed on Jobeax. Browse 30,000+ vacancies available.
Role Summary : We are seeking a skilled and experienced AI Engineer to design, build, and operate production-grade generative AI capabilities. This role focuses on developing advanced Retrieval-Augmented Generation (RAG) pipelines, sophisticated multi-agent systems, and robust automated evaluation frameworks. The ideal candidate will bridge the gap between applied data science and rigorous software engineering, focusing on building scalable, secure, and cost-efficient AI-powered https://jobeax.com/link/Hg98pRiyAXIabPoY Responsibilities : - GenAI Application Architecture : Architect and deploy production-grade LLM applications using microservices (e.g., FastAPI) and robust software engineering practices, including APIs, integration testing, and CI/CD.- Advanced RAG Engineering : Build and optimize end-to-end RAG pipelines, including document ingestion, semantic chunking strategies, metadata enrichment, vector database indexing (e.g., Azure AI Search), hybrid search (e.g., BM25 + vectors), and reranking to ground model outputs and minimize hallucinations.- Agentic AI Workflows : Design and implement agentic AI solutions, incorporating tool-calling, state management, memory architectures, planning vs. reacting agent design, reflection loops, and multi-agent coordination using frameworks like LangGraph and AutoGen. Develop human-in-the-loop systems for verification and control.- LLMOps & Lifecycle Management : Establish and manage operational standards for the AI lifecycle, including model fine-tuning, prompt versioning, semantic caching, rate limiting, and dynamic model routing to optimize for latency, cost (token economy), and performance. Implement CI/CD pipelines for AI/ML workloads.- Model Evaluation & Observability : Develop and implement automated evaluation loops using "LLM-as-a-judge" methodologies to assess faithfulness, relevance, and toxicity. Monitor model drift, performance, and reliability using frameworks such as RAGAS, TruLens, and DeepEval.- AI Safety & Governance : Implement strict guardrails (e.g., NeMo Guardrails, Llama Guard) to protect against prompt injection, data leakage, and other vulnerabilities, ensuring alignment with enterprise Responsible AI standards.- Cross-functional Collaboration : Partner closely with data scientists, platform engineers, product owners, and business stakeholders to transition prototypes into stable, production-ready https://jobeax.com/link/2rj5p3MqDPmMPA0i Skills & Experience : - Programming Languages : Expert-level Python, SQL. (Mandatory)- LLM & GenAI Concepts : 1. Deep understanding of tokenization, embeddings, prompt engineering, context windows, temperature/top-p tuning, and hallucination mitigation techniques.2. Experience with OpenAI/open-source LLM APIs, including structured outputs and function calling.- GenAI Frameworks : 1. Core : LangChain, LangGraph.2. Familiarity : LlamaIndex, CrewAI, AutoGen.- Vector Databases : 1. Experience with vector similarity search, metadata filtering, and optimization in databases such as Azure AI Search, PGVector, Pinecone, Qdrant, or Milvus.- MLOps & Platform : 1. MLflow (for model versioning, lineage, and tracking), Docker, Kubernetes.2. Experience with cloud platforms like Azure, Vertex AI (GCP), or AWS Bedrock/SageMaker.3. Proficiency with CI/CD automation and using AI coding assistants like GitHub Copilot.- Evaluation & Guardrails : 1. Experience with evaluation frameworks (e.g., RAGAS, TruLens, DeepEval, Arize/Phoenix). (ref:hirist.tech)
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