Job Description
Strong experience in: Agentic AI solutioning and Architecture; AI/ML solution architecture and deployment; Enterprise cloud infrastructure; Scalable distributed systems; Production AI platform management; Must have worked on one production grade agentic AI application on PLM background. Key Responsibilities: Design and implement enterprise AI/ML and Generative AI solutions. Build and deploy LLM-based applications, AI agents, RAG pipelines, and intelligent automation solutions. Lead AI solution deployment across cloud environments such as GCP. Develop secure, scalable, and high-availability AI infrastructure. Collaborate with engineering, DevOps, security, and business teams for enterprise AI adoption. Optimize AI model performance, infrastructure utilization, and operational efficiency. Establish MLOps, CI/CD, monitoring, and governance frameworks for AI solutions. Constantly emerging AI technologies and drive innovation initiatives. Mentor technical teams and provide architectural guidance. Support AI integration with PLM systems and engineering workflows. Strong expertise: AI & Data Skills: Machine Learning and Deep Learning; Generative AI and Large Language Models (LLMs); NLP, RAG architectures, prompt engineering, and AI agents; AI model deployment and inference optimization; Proficiency in Python and AI frameworks: PyTorch, TensorFlow, Scikit-learn, LangChain, Google ADK (Preferred), Vector databases ( MongoDB/ pgVector/ CloudSQL /Pinecone). Total Experience Expected: 08-10 years. Qualifications: BE /B TEch. Additional Information: PLM Skills: Exposure to at-least one PLM system; Understanding of engineering, manufacturing, or product lifecycle processes; Knowledge of Industry 4.0, Digital Twin, or IoT ecosystems. Soft Skills: Strong leadership and stakeholder management skills; Excellent communication and presentation abilities; Strategic thinking and problem-solving mindset.
