Why We Stand Out

Seeking a new challenge where your professional and personal aspirations are not only possible but supported? Kaufman Rossin might be just the place for you! 

Kaufman Rossin Professional Services Private Limited’s (the “Company”) offices are located in the World Trade Center (WTC) in Bangalore, Karnataka, India, and at Udyog Vihar, in Gurgaon, Haryana, India. 

The Bangalore office provides a range of services, including risk management, corporate governance, tax, assurance, and family office services. Out of the Gurgaon office, we render highly specialized back-office alternative investment services for global hedge funds and related fund types. As one of the top accounting firms in the US, our foundation is “people first”. In the words of James Kaufman, one of our founders, “We prioritize our people, their development, and their well-being. Our values are translated into action every day." 

Kaufman Rossin, headquartered in Miami, Florida has been celebrated as the Best Place to Work in South Florida more than a dozen time. The firm has grown to over 700 employees, with offices spanning the tri-county area and, sister entities, Kaufman Rossin Wealth and Kaufman Rossin Alternative Investment Services. 

The Firm is ranked 49th among the top 100 firms in the US by Inside Public Accounting 2023. Internationally, the Firm has offices in Bangalore and Haryana in India and the Ivory Coast in Africa

Think you have what it takes?

The AI Solutions Engineer joins the Innovation team to build and ship AI-powered tools across internal and client-facing work. Working from functional requirements, this person architects solutions from first principles, then builds, deploys, and iterates on them end-to-end — owning delivery in a production-ready, enterprise-ready way rather than stopping at prototypes.

The role is deliberately platform-agnostic. We care more about reasoning about cloud and AI services from fundamentals than about memorized vendor specifics, and about the ability to pick up whatever a task needs — cloud platforms, LLM APIs, agents, integrations, and workflow tooling (Claude Code, MCP servers, Azure, and more). A strong candidate uses a modern AI-assisted development workflow to move fast without sacrificing correctness, writes good tests, and treats reliability and deployment as first-class from day one.

This is a growth-oriented hire on a small, fast-moving team. Early on, the engineer wears many hats across the tool portfolio; over time, and as the team expands, they grow into a focused specialty and toward greater architecture ownership (including Azure/Entra identity design), supported by team SOPs and hands-on mentorship. We are optimizing for trajectory and self-directed learning over years on paper — someone who owns what they build, scopes ambiguity instead of waiting for a spec, and reasons from first principles

Requirements

How You’ll Contribute:

• 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.

What Skills You’ll Bring:

• 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

How You'll Stand Out:

• Azure: serverless, Azure CLI, Entra ID / identity concepts (the layer to grow into)
• Model routing by cost, latency, or capability
• MCP servers connecting tools (Asana, Confluence) to automate documentation and admin
• Azure Cognitive / AI Services, especially OCR and document processing
• GitHub CLI and a scripted dev workflow
• Client-facing or stakeholder experience

Key Systems & Tools

• Languages & frameworks: Python, JavaScript/TypeScript, FastAPI/Django
• AI / LLM: LLM APIs, agents, tool/function calling, model routing, RAG, embeddings, LangChain/LangGraph, Claude Code
• Cloud: Serverless; Azure (Azure CLI, Entra ID, Cognitive/AI Services incl. OCR), AWS (Lambda, API Gateway, EC2, ECR, Secrets Manager), GCP
• DevOps & delivery: Git, GitHub / GitHub CLI, GitHub Actions, Docker, automated testing
• Automation & docs: MCP servers, Asana, Confluence
• Data & infra: PostgreSQL, Redis, vector databases

Success in the First 90 Days

• Ramped on the team's stack, codebase, SOPs, and AI-assisted workflow (Claude Code, MCP tooling)
• Shipped 1–2 scoped deliverables to production end-to-end, with guidance
• Production-minded habits evident: tests, basic CI/CD, reliability
• Working fluently with LLM APIs, agents, and tool/function calls
• Self-scoped at least one ambiguous problem — asking sharp questions, proposing an approach
• Beginning to ramp on Azure/Entra identity design

• Contributing across internal and client-facing work

Benefits

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

We embrace authenticity. Kaufman Rossin is an equal opportunity employer. We are committed to creating a culture that reflects the diversity of our firm and clients. We encourage understanding, acceptance, and celebration among all people. That includes lifestyle, education, experience, race, ethnicity, age, religion, physical ability, sexual orientation, and gender identity. Differences make unique varieties