DevOps AI/ML Engineer

2 weeks ago


Bengaluru, Karnataka, India Cisco Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Meet the team:

The Office of the CEO at Cisco is looking for a highly expert, innovative, and self-motivated DevOps AI/ML Engineer to join our Customers Insights & Action (CIA) organization. In this critical role, you will drive the development, deployment, and production readiness of scalable AI and machine learning models, with a particular focus on Agentic and Generative AI (GenAI) and predictive capabilities. This role requires a deep understanding of AI/ML principles, hands-on experience with relevant technologies, and the ability to work effectively individually in a remote environment as well as collaborate with teams cross-functionally.

Key Responsibilities:

As an AI/ML Engineer in CIA, you will:

  • Design, build, and deploy model AI and ML pipelines as well as orchestrating multi-agent systems with memory, reflection, and planning flow.
  • Architect Retrieval-Augmented Generation (RAG) systems integrated into agentic workflows and vector databases for embeddings and retrieval.
  • Build modular, maintainable software in Python, following full software lifecycle practices (design, coding, unit testing, CI/CD).
  • Work with FastAPI or equivalent frameworks to expose agent workflows via RESTful APIs.
  • Implement embedding layers and vector DB integrations (e.g., Milvus, Weaviate, Redis) for high-perf retrieval and similarity search.
  • Conduct rigorous unit tests and integration tests, owning test coverage and reliability for agent components.
  • Stay updated with the latest advancements in AI/ML technologies, mentor junior engineers, propose architectural improvements, and participate in code reviews

Minimum Qualifications

  • Bachelors degree in Computer Science, Artificial Intelligence, Machine Learning (or related field /industry) + 8 years of DevOps experience, Masters + 6 years of related experience, or PhD + 3 years of related experience.
  • Expert-level proficiency in Python, R, or Java and as well as API frameworks (e.g. FastAPI) and AI/ML frameworks and libraries (e.g., Scikit-learn, PyTorch, TensorFlow, etc.)
  • Understanding of Agentic AI conceptsautonomy, planning loops, memory, tool use in LLM-driven agents
  • Hands-on experience with ADK, LangChain, LangGraph, LangSmith, Langgraph Studio (for graph workflows, long-term memory, stateful agents)
  • Strong understanding of CI/CD pipelines and automation tools.
  • Knowledge of cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes).
  • Proven knowledge of ML lifecycle management and model versioning.
  • Strong problem-solving skills with the ability to think critically and creatively.

Preferred Qualifications

  • Experience deploying Google Cloud Services (especially Vertex AI Agents) in production agent environments
  • Familiarity with feature stores, vector databases, or data observability platforms
  • Excellent communication, collaboration, and mentoring skills.
  • Deep expertise in CI/CD tooling and practices, including hands-on experience with systems like Jenkins, GitLab, ArgoCD, or similar.
  • Strong proficiency in Kubernetes, Docker, and cloud-native patterns in AWS, Azure, or GCP.
  • Excellent verbal and written communication skills to effectively collaborate and mentor remote team members as well as present findings.

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