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Salary
≈ $22k – $50k per year (Estimated)
Location
Remote (India)
Seniority
Senior · 6+ years exp

First seen by Alion on Oct 30, 2026.

Overview
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Impact
Profile match
Ekfrazo Technologies is an IT services company based in Bengaluru that delivers enterprise AI, data engineering, ServiceNow, Salesforce and cloud automation work for large corporate clients. Operating since 2015, it runs delivery teams in Bengaluru, Hyderabad, Noida and Pune and staffs engineers into client development programs, including data platform and generative AI projects for European and North American customers. Its openings cover Azure and senior data engineers, Java, .NET and Python full stack developers, agentic AI developers, solutions architects, database administrators, QA leads and technical project and program managers.

Role : Senior AI Developer - Agentic AI / Conversational AI.

Experience : 6 - 9 years overall, with relevant hands-on experience in developing AI/LLM-based applications.

Work Timing : 1:30 - 10:30 PM IST.

Location : Remote.

Role Overview :

We are looking for a hands-on Senior AI Developer to design, develop, and implement scalable, production-ready Conversational AI and Agentic AI solutions. The role involves building AI agents, orchestrating LLM-driven workflows, integrating enterprise systems, and implementing observability, security, and reliability practices. The candidate should be comfortable contributing to solution architecture while taking ownership of development and technical implementation.

Key Responsibilities :

- Design and develop Conversational AI and Agentic AI applications using LLMs and orchestration frameworks.

- Build and maintain AI agents, workflows, intent routing, state management, tool calling, and fallback mechanisms.

- Develop backend services and APIs to integrate AI capabilities with enterprise systems.

- Implement agent orchestration using LangGraph, LangChain, or similar frameworks.

- Develop and integrate tools using REST APIs, function calling, MCP, or structured contracts.

- Implement Retrieval-Augmented Generation (RAG) and knowledge retrieval capabilities where applicable.

- Implement LLM observability covering tracing, latency, token usage, cost, errors, and response quality.

- Develop evaluation and testing mechanisms to improve AI accuracy, reliability, and consistency.

- Ensure security, privacy, auditability, and responsible AI practices.

- Collaborate with architecture, frontend, backend, cloud, SRE, QA, and product teams.

- Participate in technical design discussions, code reviews, troubleshooting, and production support.

Required Skills :

- Strong hands-on programming experience in Python, including backend/API development using FastAPI or similar frameworks.

- Hands-on experience developing LLM-based or Conversational AI applications.

- Practical experience with LangGraph, LangChain, or equivalent agent orchestration frameworks.

- Good understanding of Agentic AI concepts, including state management, intent routing, tool calling, workflow orchestration, and error handling.

- Experience with Azure OpenAI, Azure AI Foundry (Microsoft Foundry), or equivalent cloud-hosted LLM platforms.

- Experience integrating LLM applications with REST APIs, backend services, databases, and enterprise applications.

- Understanding of prompt engineering, function calling, structured outputs, and LLM response handling.

- Experience implementing or working with LLM observability, monitoring, logging, and tracing.

- Understanding of RAG, embeddings, vector search, and knowledge retrieval patterns.

- Familiarity with authentication, authorization, security, and data privacy in AI applications.

- Strong debugging, problem-solving, and communication skills.

Nice to Have :

- Experience implementing MCP servers/clients or MCP-based integrations.

- Experience with Azure AI Search and vector databases.

- Experience with LangSmith, Langfuse, OpenTelemetry, Azure Monitor, or Application Insights.

- Experience with LLM evaluation frameworks and automated quality testing.

- Experience deploying AI applications on Azure using Docker, containers, or managed cloud services.

- Exposure to CI/CD, GitHub Actions, and production release processes.

- Experience in CRM, contact centers, customer-facing applications, or enterprise portals.

- Experience in deterministic or controlled AI workflows requiring predictable business outcomes.

Skills

Artificial Intelligence, Python, Conversational AI, Agentic AI, LangChain, FastAPI, Generative AI, RAG, AI Integration, Azure, RESTful API

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