Senior Software Engineer (AI/ML)

We are looking for a Senior Software Engineer (AI/ML) who can design, build, and scale intelligent systems — from machine learning pipelines to advanced AI agents capable of reasoning, planning, and automation. You will work on building production-grade AI models, integrating LLMs and tools, and designing agent architectures that interact with APIs, databases, and workflows. The role blends applied ML expertise with strong backend engineering and product-focused problem-solving.

Responsibilities

• Design and build autonomous or semi-autonomous AI agents that can plan, reason, and interact with tools, APIs, or external systems. - Implement agentic frameworks (e.g., LangChain, LlamaIndex, CrewAI, or custom orchestration systems). - leverage existing industry capabilities to deliver virtual assistant capabilities on top of xquic content including voice interactions. - Optimize reasoning and retrieval pipelines using embeddings, vector databases, and prompt engineering. - Develop, train, and fine-tune ML models using frameworks like PyTorch, TensorFlow, or scikit-learn. - Work on data preprocessing, feature engineering, and model evaluation for NLP, computer vision, or predictive tasks. - Build ML pipelines for training, deployment, and monitoring in production environments. - Collaborate with engineering teams to integrate AI components into backend systems and APIs. - Ensure scalable, maintainable codebases with CI/CD, observability, and cloud-native design (AWS/GCP/Azure). - Contribute to technical architecture and design reviews for AI-driven features and platforms. - Stay current with the latest in LLMs, agent frameworks, and model architectures. - Prototype and evaluate new approaches for reasoning, tool use, and adaptive behavior in agents. - Share learnings and mentor peers in ML and AI development best practices. - Bachelors Degree in Computer Science or related fields - 3+ years of experience - Strong programming skills in Python (mandatory); proficiency with PyTorch, - TensorFlow, or transformers-based models. - Experience in building or integrating AI agents (LangChain, LlamaIndex, CrewAI, custom frameworks). - Strong grasp of ML model lifecycle — data processing, model training, evaluation, deployment, and monitoring. - Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes). - Familiarity with API integrations, microservices, and asynchronous systems. - Strong understanding of vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) and retrieval architectures. - Solid software engineering fundamentals — testing, version control, and system design. - Experience with LLM fine-tuning, prompt optimization, or RAG (Retrieval-Augmented Generation) systems. - Familiarity with multi-agent systems and coordination mechanisms. - Knowledge of MLOps tools (MLflow, Kubeflow, Sagemaker, Vertex AI). - Experience in AI system observability, evaluation metrics, and continuous learning loops. - Exposure to reinforcement learning or self-improving agent architectures. Provident Fund, Medical Inpatient Facility, Medical Outpatient Facility, Paid Overtime, In-house Subsidized Lunch & Dinner, Gym Facility, Entertaining Activities, Interest Free Loan Facility, Advance Salaries and Sports Allowance.