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Bengaluru Urban · On-site · 3-6 Yrs · Oct 10
5 open roles0 posted in 7d5 in 30d
Hiring: Engineering
Job description
Overview
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).
Responsibilities
- 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
- 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
- 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
- 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
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Job application FAQ
Last updated 27 October 2026
- How do I apply for AI Engineer, GenAI and MLOps at Qfyre TechLabs?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Qfyre TechLabs may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this AI Engineer, GenAI and MLOps role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is AI Engineer, GenAI and MLOps remote or on-site in Bengaluru Urban, Karnataka?
- This listing is marked on_site with location Bengaluru Urban, Karnataka. Confirm details on the job description before applying.
- What skills matter for this AI Engineer, GenAI and MLOps role at Qfyre TechLabs?
- This is a mid-level AI Engineer, GenAI and MLOps role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.