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# IT Software Engineer

- **Company:** NICE Ltd.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Microsoft Windows, Application Programming Interfaces (APIs), Artificial Intelligence, JIRA, Unit Testing, Microsoft Azure, Code Review, Computer Programming, Continuous Integration, DevOps, Programming Tools, Github, Python (Programming Language), OAuth, Open Source Technology, Regression Testing, Azure Machine Learning, Salesforce.Com, Search Technologies, Software Engineering, TypeScript, Data Logging, Enterprise Software Applications, GitHub Copilot, Office365, ReactJS, Large Language Models, Snowflake, Grafana, Multi-Agent Systems, Prompt Engineering, IT Architecture, Rate Limiting, Git, Event Driven Architecture, AI Platforms, Information Technology, Atlassian Tools, Production Code, Virtual Agents, Restful APIs, Software Version Control, Workday, Servicenow
- **Published:** August 22, 2026
- **Apply:** https://www.dice.com/job-detail/9b1af192-fa33-4006-930c-74160de6e75a

## About the Role

2-5 years of professional software engineering experience with Python or TypeScript in production environments
Hands-on experience building and deploying LLM-powered applications: RAG pipelines, agents, tool use, or prompt engineering systems
Strong understanding of REST API design, async programming, and event-driven architecture
Experience with at least one agent or orchestration framework: LangChain, LangGraph, AutoGen, CrewAI, or equivalent
Practical knowledge of Azure services: at minimum Azure OpenAI, Azure Storage, and Azure Container Apps or AKS
Solid Git workflow: branching, PRs, code review, CI integration
Ability to write clean, tested, documented code that others can build on
Comfort working in fast-moving environments with evolving requirements
Fluency in English

Bonus:
Experience implementing MCP servers / clients or similar tool-integration protocols
Familiarity with the Anthropic Claude API, tool use patterns, and multi-turn conversation management
Experience with vector databases: Azure AI Search, pgvector, Qdrant, Weaviate, or Pinecone
Knowledge of LLM evaluation frameworks: Evals, RAGAS, LangSmith, or custom harness development
Experience with GitHub Copilot enterprise configuration, policy management, or extension development
Background in enterprise IT systems integration (Jira, ServiceNow, Salesforce, Workday, M365)
Familiarity with OpenTelemetry instrumentation and Azure Monitor / Grafana

## Description

NICE is assembling a core engineering team to build the internal AI platform that powers intelligent automation across the enterprise. As IT Software Engineer in the Orchestration AI Development team, you will move beyond using AI tools, you will build them.

You will implement the foundational components of NICE's AI architecture: the integration layer that connects enterprise systems via MCP, the agent orchestration engine, the Models Gateway, RAG pipelines, and the tooling that makes every developer at NICE more productive. Your work ships to production and is used daily by hundreds of colleagues.

This is a full-stack engineering role with a strong AI focus. You will write clean, production-quality code, collaborate closely with the Software Architect and DevOps teams, and operate with significant autonomy on technically complex problems.

How will you make an impact?

You will own and build the core components of NICE's AI platform, the integration layer, agent platform, Models Gateway, RAG pipelines, and developer tooling, working hands-on across the stack with the Architect, DevOps, and Security teams.

Build the MCP Integration Layer
Implement MCP server and client libraries that connect enterprise systems (Atlassian, Microsoft 365, ServiceNow, Workday, Salesforce, Snowflake) to AI agents
Design and expose clean tool schemas; handle auth flows (OAuth2, managed identity); implement error handling, retries, and rate limiting
Build the A2A (Agent-to-Agent) interoperability layer enabling multi-agent collaboration across the platform

Develop the AI Agentic Platform
Implement production-grade AI agent frameworks: ReAct loops, tool-augmented reasoning, multi-agent orchestration, memory and state management
Build agent harnesses for specific NICE use cases: IT helpdesk automation, procurement workflows, HR self-service, developer productivity agents
Integrate with Azure AI Foundry and Anthropic Claude API, managing context windows, tool use, streaming responses, and multi-turn conversations

Engineer the Models Gateway
Build a unified gateway abstracting multiple LLM providers (Azure OpenAI, Anthropic, open-source models via Azure ML)
Implement model routing logic, fallback chains, cost-based dispatch, latency budgeting, and per-team quota enforcement
Add logging, token metering, and usage dashboards for FinOps visibility

Build RAG Pipelines & Vector Infrastructure
Design and implement document ingestion pipelines: chunking, embedding generation, metadata enrichment, and upsert into vector stores
Build retrieval pipelines with hybrid search (dense + sparse), re-ranking, and context assembly for LLM prompts
Manage vector DB infrastructure on Azure AI Search and/other; own schema design and index optimization

Implement Prompt Management & LLM Evals
Build a prompt registry: version control, templating engine, environment promotion, and rollback
Design and run LLM evaluation pipelines: automated regression tests, hallucination detection, task-specific benchmarks
Implement human-in-the-loop feedback collection and model performance tracking dashboards

Contribute to Developer Tooling & CI/CD
Build and maintain GitHub Actions workflows for AI component testing, deployment, and rollback
Write reusable SDK / client libraries for internal teams consuming the AI platform
Integrate GitHub Copilot and Azure AI Foundry into the development workflow; document patterns for the broader R&D org

Observability & Production Operations
Instrument all AI components with OpenTelemetry: traces, metrics, and structured logs
Build Azure Monitor dashboards and alerts covering inference latency, error rates, token spend, and agent success rates
Participate in on-call rotation for critical AI platform services


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