GenAI Developer (Generative AI & Agentic AI)

Dotcom Team, LLC
United States
11 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Software Applications Microsoft Azure Computer Programming Github Python (Programming Language) Search Technologies Software Engineering SQL Databases Google Cloud Cloud Platform System
+9 more
Large Language Models Multi-Agent Systems Prompt Engineering Generative AI Backend Fastapi AI Platforms Virtual Agents Restful APIs

Requirements

The successful candidate will design, build, and deploy AI-powered applications including AI agents, copilots, retrieval-augmented generation (RAG) solutions, conversational assistants, and workflow automation platforms. This role requires a strong software engineering foundation combined with practical experience implementing production-ready AI systems within enterprise environments., * 2+ years of experience building solutions using Agentic AI technologies and Generative AI frameworks.

  • Relevant experience delivering production-ready AI applications from concept through deployment.
  • Experience developing AI solutions within healthcare, pharmaceutical, life sciences, or regulated industries.

AI & Generative AI:

  • Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents and Multi-Agent Systems, Semantic Search and Embeddings & AI Evaluation Frameworks .
  • Experience with one or more: LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, LlamaIndex

Programming & Development:

  • Python (required), SQL, REST APIs, Git/GitHub, FastAPI or equivalent backend frameworks

Cloud & Data Platforms: experience with one or more

  • Microsoft Azure, Azure OpenAI, Azure AI Foundry, AWS Bedrock & Google Cloud AI Services

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

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Structuring and scaling the backend engineering team

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Essential engineering roles in the generative AI space

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Using GitHub primitives for internal documentation and corporate operations

Kyle Daigle · Coffee With Developers

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Transitioning from software consulting to AI building

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