{"id":1990538,"url":"https://alion.io/job/goldcast-ai-engineer","title":"AI Engineer","company":{"id":2926,"name":"Goldcast","domain":"goldcast.io","url":"https://alion.io/company/goldcast","size_band":"51-200","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":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":13000,"max_usd":32000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":11},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anthropic","optional":false},{"name":"Chroma","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Gemini","optional":false},{"name":"Git","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-10-07T05:52:02Z","employer_posted_date":null,"last_verified_at":"2026-10-07T05:52:02Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"We are looking for an AI Engineer with 2-4 years of experience in applied AI, large language models (LLMs), and retrieval-augmented generation (RAG). The ideal candidate will have hands-on experience building and deploying AI-powered applications, integrating LLMs into real-world products, and developing intelligent solutions to solve business problems.\nResponsibilities:\nDesign, develop, and deploy AI-powered applications using LLMs and generative AI technologies.\nBuild and optimize RAG pipelines for document retrieval, knowledge extraction, and context-aware responses.\nIntegrate LLM APIs such as OpenAI, Anthropic, Gemini, or open-source models into applications.\nDevelop AI workflows, intelligent assistants, chatbots, and agent-based applications.\nWork with embedding models, vector databases, semantic search, and document chunking techniques.\nImplement prompt engineering, context optimization, and techniques to improve response quality.\nEvaluate and optimize AI solutions for accuracy, latency, scalability, and cost efficiency.\nCollaborate with backend and product teams to integrate AI capabilities into production systems.\nFollow best practices for AI evaluation, monitoring, testing, and responsible AI development.\nRequirements:\nExperience: 2-4 years in AI engineering, applied AI, generative AI, or a related software engineering role.\nProgramming: Strong proficiency in Python.\nLLMs and Generative AI: Hands-on experience with LLMs, LLM APIs, and generative AI applications.\nRAG: Experience building Retrieval-Augmented Generation pipelines and knowledge-based AI applications.\nAI Frameworks: Familiarity with LangChain, LlamaIndex, LangGraph, or equivalent frameworks.\nVector Databases: Experience with Pinecone, FAISS, Chroma, Weaviate, Qdrant, or similar technologies.\nMachine Learning Fundamentals: Understanding of embeddings, semantic search, NLP, and model inference.\nBackend Development: Experience with FastAPI, Flask, REST APIs, or equivalent technologies.\nApplied AI: Ability to translate business requirements into practical, scalable AI solutions.\nDeployment: Familiarity with Git, 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