What are the responsibilities and job description for the Sr. Gen AI Engineer position at Scadea?
Senior GenAI Engineer
Location: Boston, MA - 4 days a week onsite
Length: 6-10 months
Requirements Provided:
We are seeking a highly skilled Generative AI Engineer to design, build, and deploy intelligent AI agents that solve complex business challenges. The ideal candidate will have hands-on experience with modern AI development lifecycle tools, agentic frameworks, and enterprise AI platforms, with the ability to take solutions from concept through production deployment.
Key Responsibilities
Design, develop, and deploy AI agents and agentic workflows using modern Generative AI frameworks
Build scalable solutions leveraging Large Language Models (LLMs), retrieval-augmented generation (RAG), orchestration frameworks, and autonomous agents.
Develop and optimize multi-step AI workflows that integrate with enterprise systems, APIs, and business processes.
Collaborate with product, engineering, and business stakeholders to identify AI use cases and deliver production-ready solutions.
Evaluate emerging AI technologies, frameworks, and tools to improve development efficiency and solution effectiveness.
Ensure AI solutions meet enterprise standards for scalability, security, performance, and maintainability.
Required Qualifications
Experience with Microsoft Fabric and in building and deploying AI agents on Azure AI Foundry.
Strong hands-on experience with at least one AI-assisted development platform:
Claude Code
GitHub Copilot
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Windsurf
Slingshot
Experience building, testing, and deploying agentic AI solutions in enterprise environments.
Solid understanding of Large Language Models (LLMs), prompt engineering, AI workflow orchestration, tool calling, memory management, and agent architectures.
Strong software engineering fundamentals with experience in API integration, system design, and application development.
Preferred Qualifications
Proven experience designing and implementing AI agents using modern Generative AI frameworks such as:
LangGraph
LangChain
LangSmith
Similar agent orchestration and observability frameworks
Familiarity with cloud-native AI architectures and MLOps best practices.
Experience integrating AI solutions with enterprise data platforms and business applications.
Ideal Candidate
The successful candidate combines deep Generative AI expertise with strong software engineering skills and a passion for building intelligent, production-grade AI solutions. They stay current with the rapidly evolving AI ecosystem and have practical experience turning AI concepts into measurable business outcomes.
Location: Boston, MA - 4 days a week onsite
Length: 6-10 months
Requirements Provided:
We are seeking a highly skilled Generative AI Engineer to design, build, and deploy intelligent AI agents that solve complex business challenges. The ideal candidate will have hands-on experience with modern AI development lifecycle tools, agentic frameworks, and enterprise AI platforms, with the ability to take solutions from concept through production deployment.
Key Responsibilities
Design, develop, and deploy AI agents and agentic workflows using modern Generative AI frameworks
Build scalable solutions leveraging Large Language Models (LLMs), retrieval-augmented generation (RAG), orchestration frameworks, and autonomous agents.
Develop and optimize multi-step AI workflows that integrate with enterprise systems, APIs, and business processes.
Collaborate with product, engineering, and business stakeholders to identify AI use cases and deliver production-ready solutions.
Evaluate emerging AI technologies, frameworks, and tools to improve development efficiency and solution effectiveness.
Ensure AI solutions meet enterprise standards for scalability, security, performance, and maintainability.
Required Qualifications
Experience with Microsoft Fabric and in building and deploying AI agents on Azure AI Foundry.
Strong hands-on experience with at least one AI-assisted development platform:
Claude Code
GitHub Copilot
Cursor
Windsurf
Slingshot
Experience building, testing, and deploying agentic AI solutions in enterprise environments.
Solid understanding of Large Language Models (LLMs), prompt engineering, AI workflow orchestration, tool calling, memory management, and agent architectures.
Strong software engineering fundamentals with experience in API integration, system design, and application development.
Preferred Qualifications
Proven experience designing and implementing AI agents using modern Generative AI frameworks such as:
LangGraph
LangChain
LangSmith
Similar agent orchestration and observability frameworks
Familiarity with cloud-native AI architectures and MLOps best practices.
Experience integrating AI solutions with enterprise data platforms and business applications.
Ideal Candidate
The successful candidate combines deep Generative AI expertise with strong software engineering skills and a passion for building intelligent, production-grade AI solutions. They stay current with the rapidly evolving AI ecosystem and have practical experience turning AI concepts into measurable business outcomes.