About Job/Role

Lead the development of innovative Generative and Agentic AI applications.
Design and integrate AI solutions leveraging state-of-the-art models into web-based applications.
Collaborate with cross-functional teams to build, deploy, and scale AI-powered solutions that drive business value.
Explore emerging trends in AI and contribute to transformative projects.

Roles and 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 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 aligned 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 the 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.

Required Qualification

Bachelor's or master's degree in Computer Science or related fields with a strong academic track record.

Experience

3+ years of hands-on experience in building and deploying AI applications on a Python stack.

Skills

Strong knowledge of Python and related frameworks.
Experience with AI/ML frameworks and agentic platforms such as LangChain, LangGraph, AutoGen, Hugging Face, CrewAI, OpenAI APIs, PyTorch, TensorFlow, etc.
Knowledge of AI/ML workflows, including data preparation, model deployment, and optimization.
Proficiency in building and consuming RESTful APIs for connecting AI models with web applications.
Familiarity with MLOps tools and practices, including model lifecycle management, CI/CD for AI, and model monitoring.
Experience 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 emerging AI technologies, self-starter, excellent problem-solving and analytical abilities, effective communication skills.

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