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AI Engineer

AI Engineer

Collabera
4-10 Years
Not Disclosed
Early Applicant
  • Posted 20 days ago
  • Be among the first 20 applicants

Job Description

Job Title: AI Engineer / Senior AI Engineer

Job Location: Remote

Shift Timings: 12:00 PM IST to 9:00 PM IST

  • https://www.linkedin.com/showcase/collaberagtc/
  • https://collabera.com/globaltalentcenter/
  • https://www.collabera.com/
  • https://www.youtube.com/@CollaberaGTC/videos
  • https://instagram.com/collaberagtcigshid=ZWQyN2ExYTkwZQ==

Collabera, a leader in staffing Industry, is looking for AI Engineer / Senior AI Engineer Our employees work in fast paced, high energy work environment driven by our unique work culture that embraces competitiveness, passion and work hard-play hard approach to the fullest. Our clientele comprises of many Fortunes 100/500 organisations across various industry domains.

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!

More Info

Job Type:
Industry:
Employment Type:

Key Skills

Qdrant

vector databases

Pinecone

CI CD

MLOps practices

LLM-powered applications

NLP pipelines

Hugging Face models

LangChain

traditional ML techniques

Azure OpenAI GPT-based APIs

Cognitive Services

AKS

model lifecycle monitoring

Semantic Kernel

FAISS

Milvus

Weaviate

LlamaIndex

About Company

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