AI Engineer

Role: AI Engineer

Design and develop AI agents and multi-agent systems. Integrate AI solutions with enterprise platforms (JIRA, GitHub, ServiceNow, Teams, SharePoint, databases, APIs, etc.).Build workflow automation and orchestration solutions. Develop AI-accessible tools using APIs, MCP, webhooks, and event-driven architectures. Implement RAG and knowledge retrieval solutions. Design dashboards and reporting solutions using enterprise JIRA data. Optimize token usage, context management, and AI operating costs. Implement governance, monitoring, security, and human-in-the-loop controls. Bachelor’s degree in computer science, Engineering, or related field.2+ years of hands-on AI/LLM application development. Strong experience with enterprise application integrations. Technical Skills AI & Agents LLMs, Agentic AI, Multi-Agent Systems, Prompt Engineering, Retrieval-Augmented Generation (RAG), Semantic Kernel, Lang-Graph, Microsoft Auto-Gen, AI Governance, Responsible AI, GitHub Copilot, Microsoft Copilot Integration APIs, Webhooks, MCP, OAuth, Workflow Automation Knowledge Systems RAG, Semantic Search, Vector Databases, Embedding Models, Context Engineering, Retrieval Optimization Token Economy Context Engineering, Retrieval Optimization, Memory Management, Cost Optimization Data & Analytics Python, SQL, ETL/ELT, Data Pipelines, Data Modeling, Power BI, Tableau, Data Visualization, Operational Metrics & ReportingCloud & DevOps AWS/Azure, Docker, Kubernetes, CI/CD, GitHub Actions, Azure DevOps, Automated Testing, Secure SDLC, DevSecOps, Release Automation. Experience building enterprise AI platforms. Experience integrating multiple business systems and tools.• Experience with agent governance, observability, and security.• Experience delivering production-grade AI automation solutions.