Are you an AI Engineer with 1–2 years of hands-on experience in Generative AI and conversational technologies? A current hiring opportunity shared through Questhiring is looking for candidates with practical exposure to Agentic AI, Text-to-Speech (TTS), Speech-to-Text (STT), Conversational AI, Voice Agents and RAG. The role is initially remote and is expected to transition to a hybrid working model in Bangalore after the first few months. Only IIT graduates will be considered, making the educational requirement an important eligibility criterion for applicants.
📌 Job Details
🏢 Hiring Partner: Questhiring
💼 Role: AI Engineer
📍 Location: Bangalore
🏠 Initial Work Mode: Remote
🔄 Future Work Mode: Hybrid – Bangalore
💼 Experience: 1–2 Years
🎓 Education: IIT graduates only
🤖 Core Areas: Agentic AI, Conversational AI, Voice Agents, RAG, TTS & STT
📩 Application Email: sudhanshu@questhiring.com
🏢 About Questhiring
Questhiring is a recruitment and executive-search firm that connects organizations with technology and other specialized professionals. The company says it began as a small operation in India in 2015 and has grown into a recruitment and talent-solutions organization with a workforce of 100+ professionals and more than 300 clients across India and international markets. Its services include technology hiring, staffing, RPO, market mapping, interview-as-a-service and leadership hiring.
Questhiring also has a dedicated technology and product hiring practice covering roles such as software developers, data scientists, AI/ML specialists, cloud engineers, cybersecurity professionals and DevOps engineers.
⭐ Why This Role Is Good for Experience?
This opportunity can be particularly relevant for an early-career engineer who wants to move beyond basic ML experimentation into AI application engineering. The combination of Agentic AI, RAG, conversational AI and voice technologies covers several rapidly developing areas of modern AI systems.
Working with Agentic AI can expose engineers to workflows where LLMs interact with tools, make decisions and complete multi-step tasks. RAG experience can strengthen understanding of embeddings, retrieval, vector databases and grounding responses in external knowledge.
The inclusion of TTS and STT makes the opportunity different from a typical text-only GenAI role. Voice-agent development can involve speech recognition, streaming audio, latency optimization, conversation state, interruption handling and integration between AI models and communication interfaces.
🛠️ Skills Required
🔹 Python programming and strong software-development fundamentals
🔹 LLM and Generative AI application development
🔹 Agentic AI concepts, tool calling and workflow orchestration
🔹 RAG architecture, embeddings and vector search
🔹 Conversational AI and dialogue-flow design
🔹 STT technologies and speech-recognition pipelines
🔹 TTS technologies and voice-generation workflows
🔹 Voice-agent architecture and real-time interaction concepts
🔹 APIs, JSON, REST and third-party AI service integration
🔹 Prompt engineering and structured outputs
🔹 Evaluation of AI responses for accuracy, latency and reliability
🔹 Git, debugging and basic deployment practices
🔹 Familiarity with frameworks such as LangChain, LangGraph or equivalent is useful
📚 Preparation Tips
🎯 1. Build a working RAG project: Be ready to explain document ingestion, chunking, embeddings, vector search, retrieval and final response generation rather than simply saying “I worked on RAG.”
🎙️ 2. Prepare a voice-agent architecture: Understand the complete flow from user speech → STT → LLM/agent → tool/API → response generation → TTS → user.
🤖 3. Understand Agentic AI: Revise tool calling, function calling, memory, planning, state management and multi-step workflows. Be prepared to explain when an agent is useful compared with a conventional chatbot.
⚡ 4. Focus on latency: Voice applications require fast responses. Prepare concepts such as streaming, asynchronous processing, response buffering and reducing unnecessary model calls.
🧪 5. Know AI evaluation: Prepare ways to measure hallucination, retrieval quality, response relevance, task completion, latency and failure rates.
🎯 Expected Interview Rounds
🔹 Round 1 – Recruiter Screening: Experience, IIT qualification, location, current role, notice period and hands-on AI projects may be discussed.
🔹 Round 2 – Technical AI Interview: Expect questions around LLMs, RAG, Agentic AI, Python, prompts, embeddings, vector databases and API integration.
🔹 Round 3 – Practical/Project Discussion: Be prepared to explain one AI project in depth, including architecture, model selection, failures, evaluation and deployment.
🔹 Round 4 – System/AI Design Discussion: You may be asked to design a conversational AI or voice-agent system and explain scalability, latency, reliability and monitoring.
🔹 Round 5 – Client/HR Discussion: Since Questhiring works as a recruitment partner, shortlisted candidates may have additional discussions with the end client before final selection.
💰 Salary Range
The supplied vacancy does not mention a salary or compensation range, so no specific package should be assumed. Recent Questhiring technology listings show that compensation varies significantly by experience and client—for example, one 3–6 year AI Backend Engineer listing advertised ₹40–45 LPA—but that figure does not apply to this 1–2 year position.
📄 Resume Tips for This AI Engineer Role
📌 Put AI Engineer / Generative AI prominently in the headline if accurate.
📌 Mention your exact experience with Agentic AI, RAG, TTS, STT, Conversational AI and Voice Agents instead of listing only “AI/ML.”
📌 Add one or two detailed AI projects with architecture, technologies and measurable outcomes.
📌 Mention LLMs, vector databases, embeddings, LangChain/LangGraph, APIs and cloud platforms only where you have practical experience.
📌 Highlight latency, evaluation, accuracy or cost improvements if you achieved them.
📌 Include GitHub or project demonstrations if available and relevant.
📩 How to Apply
📩sudhanshu@questhiring.com
Interested candidates who meet the 1–2 years’ experience and IIT graduate requirement can share their updated resume with Sudhanshu at sudhanshu@questhiring.com. Mention your total experience, current location, notice period and strongest AI technologies in the email so the recruiter can quickly evaluate your profile.
