Role : Senior AI Ops Engineer

Job Summary :

We are looking for a Senior AI Ops Engineer to design and implement intelligent platforms, AI-driven automation solutions and operational intelligence capabilities.

The role combines Artificial Intelligence, Machine Learning, Generative AI, Agentic AI, MLOps and modern cloud-native engineering to improve operational efficiency, system reliability and business outcomes.

The ideal candidate will have strong programming and automation skills, experience with cloud-native technologies and APIs, and a keen interest in applying AI to solve complex operational challenges, automate repetitive tasks and improve system performance.

Key Responsibilities :

- Design and develop AI-driven solutions to automate operational processes, improve productivity and enhance system reliability.

- Build and integrate Generative AI and Large Language Model (LLM) applications for enterprise use cases.

- Develop AI agents and agentic workflows to automate complex tasks, decision-making and operational processes.

- Implement Retrieval-Augmented Generation (RAG) solutions and integrate AI capabilities with enterprise data sources and applications.

- Explore and implement Model Context Protocol (MCP) and related technologies for connecting AI systems with tools, data and services.

- Develop APIs and enterprise integrations to connect AI platforms with existing applications and engineering systems.

- Support MLOps and AI platform operations, including deployment, monitoring, evaluation and lifecycle management.

- Leverage operational data and analytics to identify recurring issues, detect patterns and develop proactive solutions.

- Work with Kubernetes, container platforms and cloud services to build scalable and resilient AI-powered solutions.

- Implement CI/CD pipelines, infrastructure as code and workflow automation to streamline development and deployment.

- Integrate observability platforms to monitor system health, identify operational bottlenecks and improve incident response.

- Identify failure patterns and opportunities to reduce manual intervention, operational inefficiencies and mean time to resolution (MTTR).

- Experiment with emerging AI frameworks, tools and technologies to improve automation and operational intelligence.

- Collaborate with engineering, platform, operations and business teams to translate operational challenges into technical solutions.

- Share knowledge, mentor team members and promote continuous learning and engineering best practices.

Required Skills and Experience :

- Strong programming experience in Python, Java or a similar programming language, with Python preferred.

- Understanding of Generative AI concepts, LLMs and enterprise AI application development.

- Familiarity with Agentic AI, AI agents and workflow orchestration frameworks.

- Knowledge of Retrieval-Augmented Generation (RAG), vector databases and AI-powered information retrieval.

- Understanding of Model Context Protocol (MCP) and AI tool integrations.

- Experience with API development, API integrations and enterprise application connectivity.

- Familiarity with MLOps practices and AI platform deployment, monitoring and operations.

- Knowledge of cloud-native technologies, Kubernetes and containerization.

- Exposure to cloud platforms such as AWS, Microsoft Azure or Google Cloud Platform.

- Understanding of CI/CD, infrastructure as code and automated deployment practices.

- Familiarity with observability platforms, operational analytics and workflow automation.

- Strong analytical, problem-solving and troubleshooting skills.

- Ability to learn emerging technologies quickly and collaborate effectively across technical teams.

Preferred Skills :

- Experience building and deploying production-grade AI agents and Generative AI applications.

- Hands-on exposure to RAG pipelines, vector databases and LLM integrations.

- Experience implementing AI skill files, reusable AI capabilities and orchestrated workflows.

- Knowledge of intelligent automation, operational intelligence and AI-assisted incident management.

- Experience integrating AI solutions with enterprise systems, APIs and cloud-native platforms.

- Understanding of system reliability, failure analysis, performance optimization and operational excellence.

Preferred Candidate Profile :

A technically strong engineer passionate about combining AI, automation and modern engineering practices to solve complex operational challenges.

The candidate should be comfortable experimenting with emerging AI technologies, building scalable integrations and translating operational insights into intelligent, reliable and automated solutions.