AI Engineer
at Our client is a product based org in the logitech industry
Key Responsibilities
Develop and deploy scalable AI-powered applications using the Python stack.
Leverage cutting-edge AI/ML technologies such as LangChain, LangGraph, AutoGen, Phidata, CrewAI Hugging Face, OpenAI APIs, PyTorch, TensorFlow, and other advanced frameworks to build innovative AI applications. Write clean, efficient, and well-documented code adhering to best practices.
Build and manage robust APIs for integrating AI solutions into applications.
Research and experiment with emerging technologies to discover new AI-driven use cases.
Deploy and manage AI solutions in cloud environments (AWS, Azure, GCP), ensuring security, scalability, and performance.
Collaborate with product managers, engineers, and UX/UI designers to define AI application requirements and align them with business objectives.
Apply MLOps principles to streamline AI model deployment, monitoring, and optimization.
Solve complex problems using foundational knowledge of generative AI, machine learning, and data processing techniques.
Contribute to continuous improvement of development processes and practices.
Resolve production issues by conducting effective troubleshooting and root cause analysis (RCA) within SLAs. Work with operations teams to support product deployment and issue resolution.
Requirements
Educational Background
Bachelor’s or Master’s degree in Computer Science or related fields with a strong academic track record. Experience
Technical Skills:
3+ years of hands-on experience in building and deploying AI applications on Python stack. Strong knowledge of Python and related frameworks.
Good knowledge of few of the AI/ML frameworks and agentic frameworks and platforms like LangChain, LangGraph, AutoGen, Hugging Face, CrewAI, OpenAI APIs, PyTorch, and TensorFlow etc.
Experience with AI/ML workflows, including data preparation, model deployment, and optimization. Proficiency in building and consuming RESTful APIs for connecting AI models with web applications. Knowledge of MLOps tools and practices, including model lifecycle management, CI/CD for AI, and model monitoring.
Familiarity with cloud platforms like AWS, Azure, or Google Cloud, including containerization (Docker) and orchestration (Kubernetes).
Experience with CI/CD pipelines, version control (Git), and automation frameworks. Strong understanding of algorithms, AI/ML fundamentals, and data preprocessing techniques.
Soft Skills:
Passion for exploring, experimenting and implementing emerging AI technologies. Self-starter who can independently and collaboratively in a fast-paced environment. Excellent problem-solving and analytical abilities to tackle complex challenges.
Effective communication skills to explain AI concepts and strategies to stakeholders.
Shubham Vishwakarma
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