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Research Engineer (Chatbot)
Pocket FM
Bengaluru, KSA
Full Time
Mid
3 weeks ago
PythonJavaScriptTypeScriptLLMNLPLangChain
Free
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About the Role
Pocket FM is looking for a Research Engineer with hands-on experience in designing, building, and deploying AI conversational chatbots and multi-turn dialog agents. The role involves developing end-to-end chatbot systems using LLMs, NLP, dialog orchestration, and retrieval systems.
Key Skills for This Role
PythonJavaScriptTypeScriptLLMNLPLangChain
Responsibilities
- Design and develop multi turn conversational agents using LLMs and dialog management frameworks
- Build end to end chatbot systems including intent understanding, context management, conversation memory, tool/function calling, response generation, and conversation orchestration
- Implement intelligent workflows using Agentic AI architectures, RAG, knowledge grounded conversations, and hybrid search systems
- Experiment with state of the art LLMs, open source models, and agent frameworks; fine tune or optimize models for conversational quality, latency, and cost efficiency
- Build scalable APIs and backend systems for conversational applications; integrate AI agents with enterprise systems, databases, vector stores, and external tools
- Develop automated evaluation systems for chatbot quality and user experience
Requirements
- Strong programming skills in Python (preferred) and JavaScript/TypeScript
- Experience with OpenAI APIs / Anthropic / Gemini / open source LLMs
- Hands on experience with vector databases, embedding models, NLP pipelines, conversational memory architectures
- Proven experience building and deploying AI chatbots end to end in production environments
- 2+ years in AI/ML or conversational AI engineering
Full Job Posting
Conversational AI / Multi Turn Dialog Systems
- Pocket FM is building the world's most advanced AI copilot for fiction writers.
- With 100M+ listeners globally, we sit at the intersection of generative AI, storytelling, and entertainment infrastructure.
Role Overview
- We are looking for a Research Engineer with hands on experience in designing, building, and deploying AI conversational chatbots and multi turn dialog agents end to end.
- This role combines applied research with engineering execution to build scalable, intelligent, and context aware conversational systems.
Key Responsibilities: Conversational AI Development
- Design and develop multi turn conversational agents using LLMs and dialog management frameworks.
- Build end to end chatbot systems including intent understanding, context management, conversation memory, tool/function calling, response generation, and conversation orchestration.
- Implement intelligent workflows using Agentic AI architectures, Retrieval Augmented Generation (RAG), knowledge grounded conversations, and hybrid search systems.
- Develop domain adaptive conversational experiences across structured and unstructured data sources.
Applied AI & Research
- Experiment with state of the art LLMs, open source models, and agent frameworks.
- Fine tune or optimize models for conversational quality, latency, and cost efficiency.
- Research improvements in multi agent systems, long context memory, persona consistency, hallucination reduction, dialogue evaluation, and reasoning workflows.
- Prototype and benchmark new conversational AI capabilities.
System Engineering
- Build scalable APIs and backend systems for conversational applications.
- Integrate AI agents with enterprise systems, databases, vector stores, and external tools.
- Design conversation pipelines using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, Rasa, Haystack, or custom orchestration frameworks.
- Work with vector databases such as Pinecone, Weaviate, FAISS, Milvus, or ChromaDB.
- Optimize inference pipelines for production deployment.
Evaluation & Monitoring
- Develop automated evaluation systems for chatbot quality and user experience.
- Measure conversation success rate, hallucination frequency, retrieval accuracy, user satisfaction, latency, and reliability.
- Implement observability and analytics for conversational systems.
Required Qualifications: Technical Skills
- Strong programming skills in Python (preferred) and JavaScript/TypeScript.
- Experience with OpenAI APIs / Anthropic / Gemini / open source LLMs, prompt engineering, function calling / tool usage, RAG pipelines, multi turn dialogue systems, and agent orchestration.
- Hands on experience with vector databases, embedding models, NLP pipelines, and conversational memory architectures.
Experience
- 2+ / 4+ / 6+ years (adjustable based on role level) in AI/ML or conversational AI engineering.
- Proven experience building and deploying AI chatbots end to end in production environments.
- Experience working on customer support bots, voice assistants, AI copilots, enterprise AI assistants, workflow automation agents, or domain specific conversational systems.
Preferred Qualifications
- Experience with fine tuning LLMs or training conversational models.
- Familiarity with speech systems: ASR, TTS, voice agents.
- Knowledge of reinforcement learning, ranking systems, or conversational UX.
- Experience deploying AI systems on cloud platforms: AWS, GCP, Azure.
- Understanding of AI safety, guardrails, and responsible AI systems.
What We’re Looking For
- Strong problem solving and research mindset.
- Ability to rapidly prototype and iterate on AI products.
- Passion for conversational AI and agentic systems.
- Ownership mentality with production focused engineering skills.
- Ability to work cross functionally with product, design, and ML teams.
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