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AI Engineer, GenAI and MLOps

Design, build, and deploy AI and GenAI solutions that enhance business capability, automate processes, and improve customer and employee experiences, with the ability to productionize models at scale rather than stop at a proof of concept.

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About This Role

India has roughly one qualified AI engineer for every ten open GenAI roles (TeamLease Digital), and NASSCOM projects a shortfall of close to one million AI-skilled professionals by 2027 (NASSCOM and Deloitte). This role is for an engineer who can close that gap in practice, not just on paper, with strong foundations in machine learning, LLMs, data engineering, and cloud platforms, and genuine hands-on ability to productionize models at scale for a confidential enterprise client.

What You Will Do

  • Design, build, and deploy machine learning and generative AI models, including LLMs, embeddings, transformers, and RAG pipelines
  • Develop scalable AI services and microservices using Python, REST APIs, and cloud-native technologies, optimised for performance, accuracy, and cost efficiency
  • Work with structured and unstructured datasets for feature engineering, vectorisation, and model training, and build data pipelines for training, validation, and inference
  • Collaborate with data engineering teams on data ingestion, storage, and governance
  • Implement CI/CD pipelines for ML models (MLOps), monitor model performance and drift, and implement retraining strategies
  • Manage model lifecycle, logging, and observability
  • Integrate AI systems with enterprise applications, APIs, and cloud platforms (Azure, AWS, or GCP)
  • Build Retrieval-Augmented Generation (RAG) architectures using vector databases such as Pinecone, FAISS, Weaviate, or Azure AI Search, aligned with enterprise security, compliance, and ethical AI standards
  • Work with product, engineering, domain experts, and business teams to translate requirements into technical solutions, and communicate AI capabilities and limitations to non-technical stakeholders
  • Conduct proofs of concept, demos, and conceptual solutioning

What You Need to Succeed

  • 3-5 years of relevant industry experience, with strong proficiency in Python (NumPy, Pandas, PyTorch, TensorFlow, Transformers)
  • Hands-on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, Llama, or equivalent)
  • Expertise in ML algorithms, NLP, deep learning, and vector embeddings
  • Experience with cloud platforms (Azure, AWS, or GCP) and serverless compute
  • Familiarity with MLOps tools such as MLflow, Kubeflow, Azure ML, SageMaker, or Databricks
  • Experience using vector databases such as Pinecone, Chroma, FAISS, or Azure AI Search
  • Knowledge of containerisation with Docker and Kubernetes

What Will Give You an Edge

  • Experience building RAG architectures end to end, from chunking and retrieval strategy through to generation quality
  • Comfort working within enterprise security, compliance, and ethical AI guardrails, not just a research or sandbox environment
  • Experience presenting AI capabilities and trade-offs to non-technical business stakeholders, not only to other engineers

What Qfyre Offers

  • Hands-on AI engineering ownership on a live enterprise build-out, not a prototype or internal tooling project
  • Direct exposure to production-grade LLM and RAG systems at enterprise scale
  • A confidential search process managed by a specialist talent partner, not a high-volume vendor

Skills and Technologies

PythonPyTorchLLMsRAGMLOpsVector DBAzure/AWS/GCPKubernetes
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FAQ

Questions About This Role

Common questions from candidates and applicants.

What does the application process look like for the AI Engineer, GenAI and MLOps role?+

Submit your application via the form on this page. A Qfyre domain specialist will review your profile, not an automated keyword filter, and will be in touch within two business days if there is a strong fit. We may arrange a brief introductory call before presenting your profile to the client.

Is this AI Engineer role a permanent position or contract?+

This is a Full Time position based in Bengaluru or Chennai, on-site. Specific contract terms and benefits are discussed during the briefing process once your profile has been reviewed.

What experience level is required for this AI Engineer role?+

This role requires 3-5 years of relevant experience, with hands-on exposure to LLMs, RAG pipelines, and production MLOps. If your experience is slightly outside the stated range but you have strong relevant capability, we encourage you to apply, we assess profiles holistically, not against a checklist.

Who is the hiring client for this role?+

This is a confidential search for an enterprise client undergoing active AI platform build-out. Client details are shared directly with shortlisted candidates once an initial conversation confirms mutual fit.

What are the role's core technical requirements?+

Strong Python (NumPy, Pandas, PyTorch, TensorFlow, Transformers), hands-on LLM experience (OpenAI, Azure OpenAI, Anthropic, Llama), RAG architecture using a vector database (Pinecone, Chroma, FAISS, or Azure AI Search), at least one major cloud platform, MLOps tooling, and containerisation with Docker and Kubernetes.