Job Description & Skill Requirement:

AI Solution Development & Deployment:

o Design, develop, and deploy AI-driven solutions for engineering applications using frameworks such as LangGraph or similar.

o Integrate AI capabilities into internal engineering tools to enhance productivity and automation.

Cloud AI Services Integration:

o Deploy and manage AI solutions on AWS, ensuring scalability, security, and cost optimization.

o Implement containerization, orchestration, and serverless architectures for AI workloads.

LLMOps & Testing:

o Apply LLMOps best practices for lifecycle management of large language models, including CI/CD pipelines, monitoring, and governance.

o Develop and execute testing strategies for AI applications to ensure reliability, accuracy, and compliance.

Agentic Workflows & MCP:

o Collaborate with engineering teams to design MCP-based integrations for internal tools.

o Enable agent-driven workflows that streamline engineering processes across software, hardware, and mechanical domains.

Technology Evaluation & Innovation:

o Assess and recommend commercial AI tools for engineering use cases.

o Stay informed about latest AI trends, frameworks, and technologies to guide strategic adoption.

Collaboration & Documentation:

o Work closely with multidisciplinary teams in a global environment.

o Produce clear technical documentation and contribute to knowledge-sharing initiatives.