Agentic Ai Engineer

1 day ago

Bengaluru, India Weekday AI Full time

This role is for one of the Weekday's clients Salary range: Rs 500000 - Rs 800000 (ie INR 5-8 LPA) Min Experience: 3 years Location: bangalore JobType: full-time As an Agentic AI Engineer, you will design and build advanced AI-driven voice and conversational systems using LLMs, agentic frameworks, and speech intelligence models. This role involves developing scalable AI agents, enhancing speech-processing pipelines, and integrating voice analytics into production environments. Requirements Key Responsibilities - Develop, deploy, and optimize AI agents capable of managing conversations, handling calls, and delivering intelligent, context-aware responses. - Implement and enhance speech recognition (ASR/STT) models to achieve high-accuracy, real-time audio transcription. - Build complete audio analytics pipelines including tone, emotion, and speaker analysis. - Research, fine-tune, and integrate voice intelligence models such as speaker identification, sentiment detection, and emotion recognition. - Collaborate with backend and ML teams to integrate AI and speech capabilities into production-grade applications. - Work with large-scale speech datasets for model training, testing, and performance optimization. - Continuously improve models for accuracy, latency, speed, and scalability. - Stay updated with advancements in agentic AI frameworks, speech processing, voice analytics, and multimodal AI. Must-Have Skills - Hands-on experience with agentic AI frameworks (e.g., LangChain, AutoGen, CrewAI). - Proven experience building or integrating telephony/voice AI systems (real-time audio processing, voice bots, calling AI). - Strong understanding of ASR/STT technologies (Whisper, Deepgram, AssemblyAI, or custom ASR models). - Expertise in audio signal processing (speech segmentation, MFCCs, spectrograms, emotion/tone detection, etc.). - Proficiency in Python and ML/audio libraries (PyTorch, TensorFlow, SpeechBrain, librosa, torchaudio). - Experience integrating LLMs (OpenAI, Anthropic, Gemini, etc.) for conversational intelligence. - Familiarity with APIs, SCORM, and cloud platforms (AWS, GCP, Azure). Good-to-Have Skills - Experience with TTS engines and voice cloning technologies. - Knowledge of communication protocols (WebRTC, SIP) or platforms like Twilio. - Exposure to RAG architectures and multimodal AI systems. - Experience working with vector databases (Chroma, Pinecone, Weaviate). - Strong analytical, debugging, and problem-solving abilities. Skills - Agentic AI - RAG - Speech Analytics

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