Agentic Engineer

Role Overview

We are seeking a highly skilled AI Backend Engineer with expertise in .NET (C#), Python, and API-driven architectures, combined with hands-on experience in Agentic AI frameworks (LangChain, AutoGen, or similar). The role involves building intelligent, scalable backend systems that leverage AI agents, integrate with enterprise platforms, and operate within event-driven, cloud-native environments on AWS.

Key Responsibilities

• Design and develop scalable backend services using .NET (C#) and Python
• Build and integrate AI-powered agentic systems using frameworks such as LangChain, AutoGen, or similar
• Implement Model Context Protocol (MCP) for managing AI model interactions and context orchestration
• Develop API-first architectures, exposing secure and scalable RESTful services
• Design and implement event-driven architectures using messaging systems (e.g., SQS)
• Integrate AI services with enterprise systems through REST APIs and asynchronous workflows
• Develop and manage registry and orchestration patterns for AI agents and services
• Deploy and manage applications on AWS (Lambda, S3, SQS) ensuring scalability and fault tolerance
• Collaborate with data, frontend, and product teams to deliver end-to-end AI-enabled solutions
• Ensure adherence to secure coding practices, performance optimization, and compliance standards
• Participate in code reviews, testing, and CI/CD pipelines
• Maintain technical documentation for APIs, AI workflows, and system architecture
  

• 6-8 years of experience in backend development with strong proficiency in .NET (C#) and Python
• Working knowledge of Java (for integration or legacy system support)
• Hands-on experience with Agentic AI frameworks such as:
• LangChain
• AutoGen
• or similar multi-agent orchestration frameworks
• Strong understanding of LLM-based application design and AI integration patterns
• Experience with Model Context Protocol (MCP) or similar model orchestration approaches
• Expertise in API-first development, including RESTful services and API security
• Strong experience in event-driven architectures (message queues, async processing)
• Hands-on experience with AWS services:
• Lambda (serverless compute)
• S3 (storage)
• SQS (messaging)
• Experience implementing service registry and orchestration patterns
• Strong understanding of microservices architecture and distributed systems
• Experience with version control (Git) and CI/CD pipelines
• Strong debugging, analytical, and problem-solving skills
  

• Experience with LLM providers (OpenAI, Anthropic, Azure OpenAI, etc.)
• Exposure to vector databases (Pinecone, FAISS, Weaviate, etc.)
• Familiarity with containerization (Docker, Kubernetes)
• Knowledge of prompt engineering and AI evaluation techniques
• Experience with monitoring/logging tools (CloudWatch, ELK, etc.)
• Understanding of security and governance in AI systems