Agentic Ai Engineer

1 day ago

bangalore, India Weekday AI Full time

This role is for one of the Weekday's clientsSalary range: Rs Rs ie INR 5-8 LPA)Min Experience: 3 yearsLocation: bangaloreJobType: full-timeAs 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.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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