Agentic Engineer

TechBlocks; Hyderabad; On-site; INR 1,600,000 - 2,400,000; Full time

Job summary

TechBlocks is seeking an experienced AI Backend Engineer to design and develop scalable backend services utilizing .NET (C#) and Python. This role involves working with Agentic AI frameworks like LangChain to build AI-powered solutions in AWS environments.

The ideal candidate will have 6-8 years of backend development experience, proficiency in event-driven architectures, and a strong focus on API-first development. Join us to innovate and deliver cutting-edge AI applications.

Qualifications

• 6-8 years of experience in backend development with strong proficiency in .NET (C#) and Python.
• Hands-on experience with Agentic AI frameworks such as LangChain and AutoGen.
• Strong understanding of event-driven architectures and API-first development.

Responsibilities

• Design and develop scalable backend services using .NET (C#) and Python.
• Build and integrate AI-powered agentic systems using frameworks such as LangChain.
• Deploy and manage applications on AWS ensuring scalability and fault tolerance.

Skills

Backend development

.NET (C#)

Python

Agentic AI frameworks

RESTful services

Event-driven architectures

AWS services

Tools

Git

Docker

Kubernetes

Job description

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

Required Skills Qualifications

• 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

Preferred / Nice‑to‑Have 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