Senior GenAI Engineer

Senior GenAI Engineer

Location: Boston, MA 4 days per week onsite



Contract Length: 6 10 months



Interview: Virtual

Note:

• Old LinkedIn with location - with photo
• Local candidate only

Job Summary

Our client is seeking a highly skilled Senior Generative AI Engineer to design, build, test, and deploy intelligent AI agents and agentic workflows that solve complex business challenges. The ideal candidate will have strong hands-on experience with modern Generative AI development lifecycle tools, agentic frameworks, enterprise AI platforms, and cloud-native AI architectures, with the ability to take AI solutions from concept through production deployment .

The successful candidate will combine deep Generative AI expertise with strong software engineering fundamentals and practical experience building production-grade AI solutions in enterprise environments. This individual should be comfortable working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI workflow orchestration, tool calling, memory management, autonomous and multi-agent architectures, and enterprise integrations.

Required Qualifications & Skills

• Strong hands-on experience designing, building, testing, and deploying Generative AI and agentic AI solutions .
• Experience with Microsoft Fabric and building and deploying AI agents using Azure AI Foundry .
• Hands-on experience with at least one modern AI-assisted development platform, such as:
  • Claude Code
  • GitHub Copilot
  • Cursor
  • Windsurf
  • Slingshot
• Proven experience building and deploying agentic AI solutions in enterprise environments .
• Strong understanding of LLMs, prompt engineering, AI workflow orchestration, tool calling, memory management, agent architectures, and autonomous agents .
• Strong software engineering fundamentals with experience in API integration, system design, application development, and scalable solution design .
• Experience with modern Generative AI and agent orchestration frameworks such as LangGraph, LangChain, and LangSmith , or similar agent orchestration and observability frameworks.
• Experience designing and implementing multi-step and multi-agent workflows .
• Familiarity with cloud-native AI architectures and MLOps best practices .
• Experience integrating AI solutions with enterprise data platforms and business applications .
• Strong analytical, problem-solving, collaboration, and communication skills.
• Ability to take AI concepts from initial design through development, testing, deployment, and production .
• Demonstrated ability to turn Generative AI capabilities into measurable business outcomes .

The ideal candidate combines deep Generative AI expertise, strong software engineering skills, enterprise AI experience, and a hands-on builder mindset , with a passion for developing intelligent, scalable, secure, and production-grade AI solutions.

Key Responsibilities

• Design, develop, test, optimize, and deploy AI agents and agentic workflows using modern Generative AI frameworks and technologies.
• Build scalable AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), orchestration frameworks, autonomous agents, and multi-agent workflows .
• Develop and optimize multi-step AI workflows that integrate with enterprise systems, APIs, data platforms, and business processes .
• Build and deploy AI agents using Azure AI Foundry and leverage Microsoft Fabric for enterprise AI and data capabilities.
• Apply prompt engineering, tool calling, memory management, workflow orchestration, and agent architecture patterns to build effective AI solutions.
• Collaborate with product, engineering, and business stakeholders to identify valuable AI use cases and translate business requirements into production-ready solutions.
• Build, test, troubleshoot, and deploy agentic AI applications in enterprise environments .
• Evaluate emerging Generative AI technologies, frameworks, development tools, and platforms to improve development efficiency and solution effectiveness.
• Ensure AI solutions meet enterprise standards for scalability, security, performance, reliability, maintainability, and production readiness .
• Integrate AI solutions with enterprise data platforms, business applications, APIs, and other systems.
• Apply strong software engineering practices across system design, application development, API integration, testing, deployment, and ongoing optimization.
• Stay current with the rapidly evolving Generative AI ecosystem and identify opportunities to apply new technologies and approaches to business problems.