About the Role:

We are looking for a hands-on Senior Software Engineer AI & ML to build and scale next-generation AI applications, including conversational chatbots, voice bots, and AI agents.

You will work with the latest Large Language Models (LLMs), Agentic AI frameworks, speech technologies, and cloud platforms to develop intelligent, scalable, and production-ready solutions. You will collaborate closely with Product, Engineering, and Data teams to deliver AI-powered experiences.

Key Responsibilities

- Design, develop, and deploy AI-powered applications using LLMs and Generative AI.
- Develop Agentic AI workflows using frameworks such as LangChain, LangGraph, Claude, OpenAI Agents SDK, MCP, or similar technologies.
- Build conversational AI solutions, including chatbots, voice bots, and autonomous AI agents.
- Implement RAG pipelines, prompt engineering, embeddings, and vector databases to improve response quality and accuracy.
- Develop scalable backend services and REST APIs.
- Optimize AI models and applications for latency, cost, reliability, and user experience.
- Integrate speech-to-text (STT) and text-to-speech (TTS) technologies for voice-based applications.
- Deploy AI applications on AWS using modern engineering and CI/CD practices.
- Collaborate with cross-functional teams to deliver scalable AI solutions.

Required Qualifications





- 2-3 years of overall software engineering experience, including 2+ years of hands-on experience in AI/ML and Generative AI applications.
- Strong proficiency in Python and backend development.
- Hands-on experience with leading LLMs such as OpenAI GPT, Claude, Gemini, Llama, or equivalent.
- Strong experience building RAG pipelines using vector databases such as Pinecone, Chroma, FAISS, or similar.
- Experience developing AI agents, multi-agent workflows, tool calling, function calling, and AI orchestration.
- Hands-on experience with frameworks such as LangChain, LangGraph, Claude, OpenAI Agents SDK, or similar.
- Experience with Model Context Protocol (MCP), AI evaluation frameworks, guardrails, observability, and MLOps.
- Experience integrating STT/TTS and voice platforms such as Twilio, ElevenLabs, or Exotel.
- Experience developing REST APIs, microservices, and distributed systems.
- Experience deploying cloud-native applications on AWS, Azure, or GCP.
- Hands-on experience with Docker and CI/CD pipelines.
- Robust understanding of Git, APIs, and software engineering best practices.
- Exposure to Kubernetes, Redis, Kafka, Elasticsearch, or similar technologies is an advantage.
- B.Tech / M.Tech in Computer Science, Engineering, or Information Technology ,MCA

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