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Job Description
Structured overview of role & requirementsAbout This Role
Own end-to-end design, build, deployment, and optimization of AI/ML and Generative AI enterprise solutions including data pipelines, model workflows, APIs, and evaluation.
Architect and operate secure enterprise RAG platforms and agentic systems with integration to enterprise tools and governance.
Lead technical architecture reviews, mentor engineers, and collaborate with cross-functional stakeholders for complex AI solution delivery.
Minimum Requirements
5–9 years of experience building production AI/ML and Generative AI/LLM applications.
Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, Engineering, or related field, or equivalent experience.
Mandatory hands-on experience with Python, AI/ML libraries (pandas, NumPy, TensorFlow, PyTorch, etc.), and cloud deployments on AWS or Azure including Docker and Kubernetes.
Must hold a current, role-relevant AWS AI/ML or Microsoft Azure AI certification and have hands-on production experience with the Model Context Protocol (MCP).
Ideal Candidate Profile
Deep expertise in LLMs and agentic AI architectures: prompting, embeddings, RAG, tool/function calling, orchestration, and human-in-the-loop controls.
Experienced in designing secure, distributed API services with CI/CD and infrastructure-as-code in enterprise cloud environments.
Proven ability to lead and deliver complex AI solutions in enterprise domains with strong architectural judgment and mentoring skills.