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  "job_city": "London",
  "job_state": null,
  "job_title": "GEN AI Engineer",
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  "job_country": "GB",
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  "employer_name": "Damco Solutions",
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  "job_posted_at": "1 day ago",
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  "job_description": "Summary: We're seeking GenAI Engineers to design and implement agent-based AI solutions utilizing modern frameworks. The role involves building orchestrated LLM workflows, retrieval systems, and automation components. Candidates should have a strong background in Python and experience with various AI technologies. This is a contract position based in London.\n\nKey Responsibilities:\n\nDevelop Python-based microservices and orchestration layers (Java background a plus)\nBuild agentic AI solutions using LangChain, LangGraph, RAG, and Agentic RAG\nImplement AWS Bedrock workflows, embeddings, and vector stores\nStrong hands-on Python; Java background beneficial\nLLM orchestration, embeddings, vector DBs, tool calling/agent patterns\nExperience with RAG pipelines and LangChain/LangGraph architectures\nRapidly prototype using vibe/spec-based development patterns\nIntegrate AI agents into business and engineering workflows\n\nKey Skills:\n\nProficiency in Python programming\nExperience with Java (beneficial)\nKnowledge of LangChain, LangGraph, RAG, and Agentic RAG\nFamiliarity with AWS Bedrock and vector stores\nUnderstanding of LLM orchestration and embeddings\nExperience with RAG pipelines\nAbility to rapidly prototype solutions\nIntegration skills for AI agents in workflows\n\nSalary (Rate): undetermined\nCity: London\nCountry: UK\nWorking Arrangements: undetermined\nIR35 Status: undetermined\nSeniority Level: undetermined\nIndustry: IT\n\nDetailed Description From Employer:\nRole: GEN AI Engineer Location: London Type: Contract Role Summary We're looking for GenAI Engineers to design and implement agent-based AI solutions using modern frameworks. You'll build orchestrated LLM workflows, retrieval systems, and automation components. Responsibilities Develop Python-based microservices and orchestration layers (Java background a plus) Build agentic AI solutions using LangChain, LangGraph, RAG, and Agentic RAG Implement AWS Bedrock workflows, embeddings, and vector stores Strong hands-on Python; Java background beneficial LLM orchestration, embeddings, vector DBs, tool calling/agent patterns Experience with RAG pipelines and LangChain/LangGraph architectures Rapidly prototype using vibe/spec-based development patterns Integrate AI agents into business and engineering workflows",
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  "employer_website": "https://www.damcogroup.com",
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  "job_employment_type": "Full–time and Contractor",
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  "job_posted_at_timestamp": 1774569600,
  "job_posted_at_datetime_utc": "2026-03-27T00:00:00.000Z"
}