Senior AI Engineer

8 hours ago

Hyderabad, Telangana, India Aquaexchange Agritech Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Job Description: Senior AI Engineer

Experience: 3 to 6 Years

Location: Hyderabad

Employment Type: Full-time

About the Role

We are looking for a Senior AI Engineer to lead the development and deployment of advanced AI solutions. This role requires strong expertise in LLMs, LangChain, vector databases, MLOps, and modern AI frameworks. You will design and integrate intelligent systems into production environments, while mentoring junior engineers and collaborating with cross-functional teams.

Key Responsibilities

  • Design, train, and deploy machine learning and deep learning models.
  • Work with Large Language Models (LLMs) and frameworks such as LangChain, LLaMA, GPT, Hugging Face.
  • Develop AI agents and workflows using MCP (Model-Compute-Pattern) and orchestration tools.
  • Implement retrieval-augmented generation (RAG) pipelines with vector databases (Pinecone, Weaviate, FAISS, Milvus, etc.).
  • Build and maintain data pipelines for training, validation, and monitoring.
  • Integrate AI models and APIs into backend systems , GraphQL, REST, WebSockets).

  • Deploy and scale models using Docker, Kubernetes, and cloud services (AWS/GCP/Azure).

  • Apply MLOps practices (MLflow, Kubeflow, Airflow, CI/CD) for efficient model lifecycle management.

  • Ensure performance, scalability, and cost optimization of AI systems.
  • Collaborate with backend, data, and product teams to deliver AI-driven features.
  • Mentor and guide junior AI engineers in modern AI technologies.

Required Skills & Qualifications

  • 36 years of experience in AI/ML development and deployment.
  • Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).
  • Strong hands-on with LLMs and LangChain for building intelligent applications.
  • Knowledge of vector databases and RAG pipelines.
  • Familiarity with MCP (Model-Compute-Pattern) and AI agent design.
  • Experience with SQL/NoSQL/Graph databases (Postgres, MongoDB, Neo4j).
  • Strong background in Docker, Kubernetes, and cloud-native deployment.
  • Practical understanding of MLOps (model versioning, monitoring, CI/CD).
  • Ability to translate business requirements into production-ready AI solutions.

Nice-to-Have

  • Experience with real-time inference systems.
  • Exposure to reinforcement learning, multi-modal AI (text, vision, audio).
  • Knowledge of data streaming frameworks (Kafka, Flink, Spark).
  • Hands-on with AI security, prompt injection prevention, and compliance best practices.

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