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.
Requirements
Bachelors Degree in Computer Science or related fields3+ years of experienceStrong 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.Benefits
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.