Senior Artificial Intelligence Engineer

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• https://www.linkedin.com/showcase/collaberagtc/

• https://collabera.com/globaltalentcenter/

• https://www.collabera.com/

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AI Engineer / Senior AI Engineer

About the Role

We are expanding our AI team to build, scale and enhance our production-grade AI systems. As an AI Engineer, you will work across the full spectrum of AI traditional ML, NLP, LLM-powered applications, conversational AI, multimodal AI (text, audio, video), agentic architectures, and evolving AI use cases — with a strong focus on Azure-based deployment. This role is about applying and integrating AI technologies into enterprise solutions and workflows, driving efficiency, automation, and actionable insights across business functions.

Key Responsibilities

• Design, build, and deploy AI/ML models and applications on Azure (Azure ML, Cognitive Services, AKS, Functions).
• Develop and integrate LLM-powered applications (Azure OpenAI, GPT-based APIs, Hugging Face models).
• Build and deploy chatbot and conversational AI systems for enterprise productivity, knowledge and information management.
• Develop traditional ML models (classification, prediction, recommendation) and combine them with LLM/NLP workflows.
• Architect and implement agentic AI systems and orchestration workflows.
• Work with vector databases (Pinecone, Weaviate, Milvus, FAISS, Qdrant) for retrieval-augmented generation (RAG).
• Explore and implement emerging AI use cases such as video analytics, emotion/sentiment analysis, and ranking systems.
• Integrate AI solutions with enterprise applications and platforms (ERP, CRM, ITSM, HR systems).
• Build and integrate APIs/web services for enterprise applications.
• Ensure production readiness: CI/CD, monitoring, observability, performance tuning, and cost optimization.
• Collaborate with product, engineering, and IT teams to deliver end-to-end AI solutions.

Required Skills & Experience

• 4–10 years in software/AI engineering with strong Python skills.
• Hands-on experience with traditional ML techniques, NLP pipelines, and using LLMs via APIs and SDKs.
• Prior experience building chatbots or conversational AI systems in production.
• Familiarity with ML/AI libraries and toolkits (PyTorch, TensorFlow, Hugging Face, LangChain/LlamaIndex/Semantic Kernel).
• Proven track record deploying AI applications on Azure.
• Experience with vector databases and embeddings for retrieval.
• Exposure to agentic systems and orchestrating multi-step reasoning.
• Skilled at building APIs/microservices and integrating AI into enterprise systems.
• Familiar with MLOps practices: CI/CD, model lifecycle, monitoring, and scaling.

Preferred Qualifications

• Experience with agent frameworks (LangChain, AutoGen, Semantic Kernel, Haystack).
• Knowledge of prompt design, RAG workflows, and LLM integration best practices.
• Strong background in NLP pipelines (NER, sentiment, text classification, search).
• Experience with multimodal AI (text, audio, video), computer vision, or emotion analysis.
• Knowledge of data pipelines/ETL for AI workloads.
• Understanding of enterprise AI security, compliance, and governance.
• Azure certifications or prior enterprise-scale Azure deployments.

Looking forward to hearing from you!