Forward Deployed AI Engineer

nSearch Global; Abu Dhabi; On-site; AED 300,000 - 550,000; Full time

Job summary

nSearch Global seeks an experienced AI software engineer to design and deliver enterprise-grade agentic AI applications from discovery to production.

You will implement RAG pipelines, connect agents to tools and APIs via REST/OpenAPI, and ensure reliability with structured LLM patterns.

Candidates should have 5+ years building production software with GenAI/LLMs and hands-on experience with MCP-style tool communication.

Qualifications

• Degree in Computer Science, Software Engineering, Data Science, AI/ML or related field.
• 5+ years building production-grade software, including 3+ years with GenAI and LLMs.
• Minimum 1 year of hands-on Agentic AI experience with a proven record of taking agentic solutions to production.
• Hands-on experience or strong working knowledge of MCP for connecting agents to tools, systems, APIs and data.
• Experience with async programming, FastAPI, Pydantic, Git, CI/CD, testing, error handling and logging.
• Experience with at least one agent framework or enterprise AI platform such as LangGraph, Semantic Kernel, CrewAI, AutoGen, OpenAI Agents SDK, Microsoft Foundry, Amazon Bedrock AgentCore or Google Vertex/Gemini.
• Experience with vector databases/search platforms such as Azure AI Search, pgvector, Pinecone, Weaviate or OpenSearch.

Responsibilities

• Understand the business need before building and take solutions from discovery through production.
• Design, build, deploy and continuously improve enterprise-grade agentic AI applications.
• Build agents that reason across multiple steps, call tools and APIs, manage context, handle exceptions and support human-in-the-loop workflows.
• Design and implement RAG pipelines covering ingestion, chunking, embeddings, vector search, retrieval tuning, grounding and source traceability.
• Build MCP-based integrations and connect agents to backend systems through REST/OpenAPI, webhooks and event-driven patterns with secure authentication.
• Apply structured LLM patterns including tool calling, schema-validated outputs, retries, fallbacks and guardrails.
• Coordinate with Business Product Owners, AI Value Architects and other squads.
• Own end-to-end delivery of significant AI use cases and set the pace on quality, evaluation and reliability.

Skills

GenAI & LLMs

Agentic AI

Async programming

REST/OpenAPI

Tool calling

CI/CD

Testing

Education

Degree in Computer Science / Software Engineering / Data Science / AI

Tools

FastAPI

Pydantic

Git

CI/CD tools

LangGraph

Semantic Kernel

OpenAI Agents SDK

Microsoft Foundry

Amazon Bedrock AgentCore

Job description

• Understand the business need before building and take solutions from discovery through production.
• Design, build, deploy and continuously improve enterprise-grade agentic AI applications.
• Build agents that reason across multiple steps, call tools and APIs, manage context, handle exceptions and support human-in-the-loop workflows.
• Design and implement RAG pipelines covering ingestion, chunking, embeddings, vector search, retrieval tuning, grounding and source traceability.
• Build MCP-based integrations and connect agents to backend systems through REST/OpenAPI, webhooks and event-driven patterns with secure authentication.
• Apply structured LLM patterns including tool calling, schema-validated outputs, retries, fallbacks and guardrails.
• Coordinate with Business Product Owners, AI Value Architects and other squads.
• Own end-to-end delivery of significant AI use cases and set the pace on quality, evaluation and reliability.

Requirements:

• Degree in Computer Science, Software Engineering, Data Science, AI/ML or a related technical field, or equivalent practical experience.
• 5+ years building production-grade software, including 3+ years with GenAI and LLMs.
• Minimum 1 year of hands-on Agentic AI experience with a proven record of taking agentic solutions to production.
• Hands-on experience or strong working knowledge of MCP for connecting agents to tools, systems, APIs and data.
• Experience with async programming, FastAPI, Pydantic, Git, CI/CD, testing, error handling and logging.
• Experience with at least one agent framework or enterprise AI platform such as LangGraph, Semantic Kernel, CrewAI, AutoGen, OpenAI Agents SDK, Microsoft Foundry, Amazon Bedrock AgentCore or Google Vertex/Gemini.
• Experience with vector databases/search platforms such as Azure AI Search, pgvector, Pinecone, Weaviate or OpenSearch.