Cynet Systems Inc
Job Description:
Design end-to-end AI architectures that integrate GenAI and Agentic capabilities into enterprise platforms. Build innovative AI solutions across on-premise and cloud infrastructures. Lead the development of RAG pipelines and hybrid inferencing strategies. Evaluate and implement agent-based orchestration frameworks. Act as a thought leader on GenAI, responsible AI, and system governance. Collaborate with technical teams for model development, deployment, and training. Engage stakeholders through Client sessions and executive presentations. Mentor internal teams and contribute to knowledge-sharing efforts. Requirement/Must Have:
Hands-on experience with GenAI or LLM-based solution design. Experience designing AI solutions for industries such as financial services, healthcare, manufacturing, and energy. Deep expertise with LLMs such as OpenAI, Mistral, Claude, and LLaMA. Familiarity with vector databases such as FAISS and Pinecone. Proficiency in GenAI tools including LangChain, LlamaIndex, and Transformers. Experience with agentic frameworks like AutoGen, CrewAI, and AutoGPT. Strong Python programming skills and experience with cloud platforms like Azure, AWS, or GCP. Knowledge of responsible AI principles and compliance frameworks. Experience:
15+ years in enterprise technology, consulting, or solution architecture roles. 3+ years of hands-on experience in GenAI or LLM-based solution design. Proven track record working with banks, insurers, fintechs, and asset managers. Demonstrated ability to lead architecture reviews and solution blueprinting. Responsibilities or Duties:
Lead solution architecture for GenAI and Agentic AI systems. Select appropriate GenAI technologies to meet client needs. Conduct Client sessions and co-creation workshops with business and IT stakeholders. Translate AI capabilities into business outcomes and roadmaps. Ensure AI system compliance, security, and explainability. Mentor and guide internal teams through enablement sessions. Should Have:
Excellent communication skills. Ability to build client confidence and lead technical conversations. Strong leadership and stakeholder management skills. Skills:
LLMs (OpenAI, Claude, LLaMA, etc.). Agentic frameworks (AutoGen, CrewAI). Vector databases (FAISS, Pinecone). Cloud platforms (Azure, AWS, GCP). Python, LangChain, Transformers, LlamaIndex. Qualification or Education:
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
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Design end-to-end AI architectures that integrate GenAI and Agentic capabilities into enterprise platforms. Build innovative AI solutions across on-premise and cloud infrastructures. Lead the development of RAG pipelines and hybrid inferencing strategies. Evaluate and implement agent-based orchestration frameworks. Act as a thought leader on GenAI, responsible AI, and system governance. Collaborate with technical teams for model development, deployment, and training. Engage stakeholders through Client sessions and executive presentations. Mentor internal teams and contribute to knowledge-sharing efforts. Requirement/Must Have:
Hands-on experience with GenAI or LLM-based solution design. Experience designing AI solutions for industries such as financial services, healthcare, manufacturing, and energy. Deep expertise with LLMs such as OpenAI, Mistral, Claude, and LLaMA. Familiarity with vector databases such as FAISS and Pinecone. Proficiency in GenAI tools including LangChain, LlamaIndex, and Transformers. Experience with agentic frameworks like AutoGen, CrewAI, and AutoGPT. Strong Python programming skills and experience with cloud platforms like Azure, AWS, or GCP. Knowledge of responsible AI principles and compliance frameworks. Experience:
15+ years in enterprise technology, consulting, or solution architecture roles. 3+ years of hands-on experience in GenAI or LLM-based solution design. Proven track record working with banks, insurers, fintechs, and asset managers. Demonstrated ability to lead architecture reviews and solution blueprinting. Responsibilities or Duties:
Lead solution architecture for GenAI and Agentic AI systems. Select appropriate GenAI technologies to meet client needs. Conduct Client sessions and co-creation workshops with business and IT stakeholders. Translate AI capabilities into business outcomes and roadmaps. Ensure AI system compliance, security, and explainability. Mentor and guide internal teams through enablement sessions. Should Have:
Excellent communication skills. Ability to build client confidence and lead technical conversations. Strong leadership and stakeholder management skills. Skills:
LLMs (OpenAI, Claude, LLaMA, etc.). Agentic frameworks (AutoGen, CrewAI). Vector databases (FAISS, Pinecone). Cloud platforms (Azure, AWS, GCP). Python, LangChain, Transformers, LlamaIndex. Qualification or Education:
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
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