AI Solutions Engineer

Kaufman Rossin

AI Solutions Engineer in Kaufman Rossin's Innovation team building AI-powered tools. Architecting, deploying, and iterating solutions across internal and client-facing work.

Posted 7/22/2026full-timeBengaluru • 🇮🇳 IndiaJuniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong capabilities in Python development, cloud services, and AI-assisted workflows, with a focus on production-ready delivery and end-to-end ownership of systems. Proficient in deploying reliable solutions while ensuring testability and iteration.

Highest-signal resume keywords

Python DevelopmentCloud Services UnderstandingLLM API IntegrationGit/GitHub ProficiencyCI/CD Pipeline Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonServerless ArchitectureCloud ServicesLLM APIsTest-Driven Development

Soft Skills

Self-Directed LearningProblem Solving

Tools & Technologies

Claude CodeGitHub ActionsMulti-Cloud Setup

Industry Keywords

Production-Ready DeliveryEnd-to-End OwnershipAutomationIntegrationWorkflow Tools

Tech Stack

Tools & technologies

AzureCloudPython

About the role

Key responsibilities & impact

Translate functional requirements (internal or client-facing) into working systems — architecting from first principles, then building, deploying, and iterating end-to-end.
Work cloud- and tool-agnostic, reasoning from fundamentals across a multi-cloud setup; pick up whatever a task needs (cloud, AI tooling, integrations, agents, workflow tools like Claude Code, MCP, Azure), including automating documentation and admin overhead.
Own production-ready delivery — deployments and iterations, not prototypes. Wear many hats early on a small team, then grow into a focused specialty as it expands.

Requirements

What you’ll need

Minimum experience: 1+ years (trajectory prioritized over tenure)
Strong Python (backend + front-end-adjacent) with demonstrated end-to-end ownership, not just contribution
Serverless and cloud services understood from first principles; platform-agnostic
Hands-on with LLM APIs: multiple models, agents, tool/function calls, matching model to task
Comfort with an AI-assisted development workflow (e.g., Claude Code) — speed and correctness
Git/GitHub and basic CI/CD pipelines (GitHub Actions or equivalent)
Writes good tests; treats testability as first-class
Production-minded on deployment, reliability, and iteration from the start Fast, self-directed learner who reasons from fundamentals

Benefits

Comp & perks

Work-Life Balance
People First Company
Hybrid work policy
Working directly with peers in the US