Job Summary
We are looking for a AgenticAI/GenAI Engineer with strong experience in building and deploying GenAI/AgenticAI applications. The ideal candidate has hands-on expertise with modern AI stacks, Agent Development Kit, MCP. A2A , cloud platforms, vector databases and Retrieval-Augmented Generation (RAG).
Key Responsibilities
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Develop solutions using LLMs (Azure OpenAI, Google Gemini, OpenAI APIs or similar) and Agent Development Kits (OpenAI Agent SDK/Google ADK/Langchain/Langraph).
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Build RAG pipelines using LangChain, LlamaIndex, or similar tools.
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Implement document processing, embeddings, vector search, and hybrid semantic search.
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Deploy GenAI applications on Azure ML Studio, Vertex AI, AWS, or using FastAPI + Docker/Kubernetes.
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Integrate CI/CD workflows using GitHub Actions, Azure DevOps, etc.
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Collaborate with product and engineering teams to deliver scalable, secure, and high-performance AI systems.
Required Skills
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Strong proficiency in Python and backend AI development.
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Experience with LLMs (Azure OpenAI, Gemini, etc.) and any Agent development kit.
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Knowledge of embeddings (Sentence-Transformers, OpenAI Embeddings, etc).
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Hands-on experience with vector DBs like Pinecone, Qdrant, Weaviate, Chroma, FAISS, etc.
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Familiarity with hybrid search tools such as Azure AI Search, OpenSearch or similar.
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Experience deploying applications on cloud PaaS/IaaS or Kubernetes.
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Working knowledge of CI/CD and LLM/MLOps practices.
Nice to Have
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Experience with evaluations, prompt engineering, fine-tuning and agent workflows.