{"id":2803441,"url":"https://alion.io/job/hrizen-generative-ai-engineer-python","title":"Generative AI Engineer - Python","company":{"id":3806664,"name":"HriZen","domain":"hrizen.com","url":"https://alion.io/company/hrizen","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":17000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":31},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI 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enterprise-grade GenAI applications.\n\nKey Responsibilities : \n\n- Design, develop, and deploy Generative AI applications using Python.\n\n- Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval.\n\n- Integrate Large Language Models (OpenAI GPT, Claude, Llama, Gemini, Mistral, etc.) into production applications.\n\n- Develop AI agents and conversational assistants using LangChain, LangGraph, LlamaIndex, or similar frameworks.\n\n- Design REST APIs and microservices using FastAPI or Flask.\n\n- Work with vector databases such as Pinecone, ChromaDB, FAISS, Weaviate, or Milvus.\n\n- Build prompt engineering workflows and optimize prompts for accuracy and performance.\n\n- Fine-tune open-source language models where required.\n\n- Develop scalable backend services for AI applications.\n\n- Deploy AI solutions on AWS, Azure, or GCP using Docker and Kubernetes.\n\n- Collaborate with Data Scientists, ML Engineers, and Product teams to deliver AI-driven solutions.\n\n- Monitor model performance, latency, and cost optimization.\n\n- Implement security, governance, and responsible AI practices.\n\nRequired Skills : \n\n- Strong Python programming skills.\n\n- Experience with FastAPI, Flask, or Django.\n\n- Hands-on experience with Large Language Models (LLMs).\n\n- Experience with OpenAI API, Azure OpenAI, Anthropic Claude, Gemini, or open-source models.\n\n- Strong knowledge of Prompt Engineering.\n\n- Experience with LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGen.\n\n- Hands-on experience building RAG-based applications.\n\n- Knowledge of embeddings and semantic search.\n\n- Experience with vector databases (FAISS, Pinecone, ChromaDB, Weaviate, Milvus).\n\n- Experience with SQL and NoSQL databases.\n\n- REST API development experience.\n\n- Git and CI/CD pipelines.\n\n- Docker and Kubernetes.\n\n- Cloud platforms (AWS, Azure, or GCP).\n\nPreferred Skills : \n\n- Knowledge of machine learning fundamentals.\n\n- Experience with Hugging Face Transformers.\n\n- Model fine-tuning using LoRA or PEFT.\n\n- Experience with MLflow or model lifecycle management.\n\n- Knowledge of Kafka or RabbitMQ.\n\n- Experience with Elasticsearch or OpenSearch.\n\n- Familiarity with monitoring tools such as Prometheus and Grafana.\n\nQualifications : \n\n- 3 to 7 years of software development experience.\n\n- Strong experience in Python backend development.\n\n- At least 1 to 2 years of hands-on experience building Generative AI applications.\n\n- Excellent problem-solving and communication skills.\n\n- Experience working in Agile/Scrum environments.\n\nNice to Have : \n\n- Experience with AI Agents and multi-agent systems.\n\n- Knowledge of MCP (Model Context Protocol).\n\n- Experience with AI workflow orchestration.\n\n- Exposure to enterprise AI governance and responsible AI frameworks.\nSkills\nGenerative AI, Artificial Intelligence, Python, LLM, RAG, VectorDB, OpenAI, AWS, Flask, Django, 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