Unify Technologies - Senior Engineer - AI & Backend Systems

About The Role

Required Experience & Skills

• 6+ years in backend software design and development, with at least 2 years working on AI based systems & solutions
• Very strong in Python development with proven experience designing and building scalable, high-performance backend systems using Python, and deep expertise in FastAPI, Flask and other similar Python frameworks.
• Strong hands-on experience in developing and maintaining connectors to third-party APIs, ensuring secure, reliable, and efficient data exchange.
• Experience developing & deploying to the cloud (AWS/GCP/Azure) using infrastructure components like Docker, Kubernetes etc.
• Expertise working with AI-assisted development tools (e.g., Cursor, GitHub Copilot, Claude Code etc. ) and using human-in-the-loop review processes to ensure code safety and reliability.
• Strong grounding in the software engineering lifecycle, with knowledge of clean architecture, testing strategies, version control, CI/CD, and cloud-native backend engineering best practices.
• Experience working with AI frameworks or libraries (Transformers, LangChain, OpenAI APIs etc.) and hands-on experience developing AI-powered systems is a strong plus.
• Exposure to integrating Retrieval-Augmented Generation (RAG) systems and experience implementing agent workflows/protocols (e.g., MCP) is a plus.
• Ability to work in a rapidly iterative, experiment-driven environment with a tightly knit, cross-functional team
  

Key Responsibilities

• Work collaboratively with senior members in the team to design integrations as per the requirements and deploy these into the solution workflows.
• Develop integrations into various source and output systems using APIs, protocols like MCP and other available interfaces.
• Collaborate with data engineers & AI engineers in the team to integrate the core LLM solution and the data platform with the API infrastructure.
• Drive the usage of AI coding assistants or agentic coding tools in the team, while establishing appropriate development & coding processes and standards for tool usage.
• Participate in reviewing the code developed for the applications, including APIs and services built on LLMs to ensure robustness and reliability.
• Contribute to establishing engineering best practices and standards for performance, code quality, and reliability