AI Engineer

We are seeking an AI Engineer with strong software engineering foundations and hands-on experience in Generative and Agentic AI. In this role, you will design and build production-grade AI systems powered by large language models and intelligent agents.

You will develop scalable AI workflows, integrate autonomous agents into real-world applications, and help translate cutting-edge AI capabilities into reliable business solutions. This position is ideal for engineers who enjoy combining experimentation with disciplined engineering to deliver impactful AI-driven products.

• 2-4 years of professional software development experience (Dotnet/React/Full-stack).
• Minimum 2 years of hands-on experience building applications using Generative AI or agentic AI systems.
• Strong proficiency in Python and backend engineering principles.
• Experience designing RESTful APIs and scalable service architectures.
• Practical experience with LLM APIs, embeddings, vector search, or RAG pipelines.
• Familiarity with agent frameworks and autonomous decision workflows.
• Understanding of data structures, system design, and performance optimization.
• Strong analytical thinking and problem-solving skills.

• Design, develop, and deploy production-ready applications leveraging Generative AI and agentic AI frameworks.
• Build intelligent workflows using LLMs, multi-agent coordination, and orchestration pipelines.
• Implement prompt engineering strategies, retrieval-augmented generation (RAG), and contextual memory systems.
• Implement various AI coding techniques (context-driven, spec-driven development etc.).
• Implement and utilize Model Context Protocol (MCP) patterns to enable structured communication between agents, tools, and systems.
• Develop evaluation pipelines to measure accuracy, safety, and performance of AI systems.
• Optimize latency, cost efficiency, and scalability of AI-powered workflows.
• Collaborate with product managers, data teams, and software engineers to deliver AI features.
• Ensure reliability through testing, logging, monitoring, and observability of AI behavior.
• Contribute to architectural decisions, coding standards, and best practices.
• Act as an AI trailblazer for development teams by promoting best practices, reusable patterns, and adopting AI-driven engineering approaches.
• Apply AI governance principles to ensure responsible model usage, auditability, and transparency in AI workflows.
• Research emerging AI tools and frameworks to continuously improve system capabilities.
• Document AI workflows and maintain reproducible engineering processes.