Position Summary

The Generative AI Solutions Engineer is responsible for building AI-powered backend features and automation components using modern LLM APIs. The role requires strong backend engineering fundamentals in any mainstream programming language (Python, Node.js, PHP or similar), the ability to analyze requirement documents, convert them into technical structure, and deliver rapid proof-of-concept implementations.

The work focuses on creating practical solutions, integrating external APIs, generating structured outputs, and developing reusable components that accelerate software development and reduce manual effort.

This is not a research or academic AI position — it is a hands-on engineering role focused on real-world business and product needs.

Key Responsibilities

• Build backend services using Python or Node.js.
• Integrate with LLM APIs (OpenAI, Claude, Mistral and so on).
• Process requirement documents and extract structured information.
• Generate module-level breakdowns and engineering estimations.
• Create API or backend prototypes for high-level requirements.
• Build helper scripts/tools that reduce repetitive engineering work.

Required Technical Skills

• Strong backend engineering skills (Python / Node.js / PHP or similar)
• Experience building and consuming REST APIs
• SQL basics and database design understanding
• Ability to produce backend prototypes rapidly
• Experience working with JSON and external APIs
• Familiarity with LLM APIs (OpenAI, Claude, Mistral or similar)

Nice-to-Have

• LangChain or LlamaIndex experience.
• Some prompt engineering experience.
• Docker basics.
• Internal developer tooling experience.
• Ability to analyze incomplete requirements.

Fit Profile

Best fit for someone who:

• likes real engineering more than research,
• enjoys prototyping solutions,
• understands system behavior and data flows,
• can operate with limited documentation,
• can deliver results within short timeframes.

What this role is NOT

• Not academic AI research
• Not ML model training
• Not data science
• Not RPA automation
• Not prompt-engineering-only

Why the role is attractive

• build working AI-first solutions
• solve real customer challenges
• high autonomy, low bureaucracy
• meaningful systems, not demos
• highly visible impact

This is NOT a research job. You will build real AI-powered software that solves real business problems.