Line of Service
Industry/Sector
Specialism
Management Level
We're looking for a Senior AI/ML Engineer who can design, build, and deploy scalable ML, GenAI, and Agentic AI systems across cloud environments with strong focus on productionization, automation, and business impact. You'll work across demand forecasting, RAG-based intelligent applications, autonomous multi-agent systems, and enterprise AI integration.
Responsibilities:
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Build end-to-end ML/AI pipelines (data → model → deployment → monitoring)
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Develop and deploy ML, Deep Learning, NLP, and GenAI models in production
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Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering
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Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory
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Build and optimize time series forecasting models (demand forecasting, inventory planning)
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Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance
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Optimize models for performance, cost, and latency
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Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications
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Design scalable LLM inference architectures for efficient deployment
-
Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams
-
Debug, optimize, and enhance ML models for quality and performance improvements
-
Mentor team members and present technical findings to diverse audiences
-
Stay current with AI/GenAI trends and evaluate emerging tools and frameworks
Mandatory skill sets:
-
Build end-to-end ML/AI pipelines (data → model → deployment → monitoring)
-
Develop and deploy ML, Deep Learning, NLP, and GenAI models in production
-
Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering
-
Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory
-
Build and optimize time series forecasting models (demand forecasting, inventory planning)
-
Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance
-
Optimize models for performance, cost, and latency
-
Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications
-
Design scalable LLM inference architectures for efficient deployment
-
Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams
-
Debug, optimize, and enhance ML models for quality and performance improvements
-
Mentor team members and present technical findings to diverse audiences
-
Stay current with AI/GenAI trends and evaluate emerging tools and frameworks
Preferred skill sets:
-
Build end-to-end ML/AI pipelines (data → model → deployment → monitoring)
-
Develop and deploy ML, Deep Learning, NLP, and GenAI models in production
-
Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering
-
Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory
-
Build and optimize time series forecasting models (demand forecasting, inventory planning)
-
Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance
-
Optimize models for performance, cost, and latency
-
Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications
-
Design scalable LLM inference architectures for efficient deployment
-
Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams
-
Debug, optimize, and enhance ML models for quality and performance improvements
-
Mentor team members and present technical findings to diverse audiences
-
Stay current with AI/GenAI trends and evaluate emerging tools and frameworks
Years of experience required:
7-12 years
Education qualification:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (60% above)
Education
Certifications
Required Skills
Optional Skills
Desired Languages
Travel Requirements
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date
