AN

anarock

AI Engineer

Bengaluru · Staff/Principal

Expect moderate competitionVerified listingPosted 18d ago

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Skills required

40 listed

Retrieval-Augmented Generation (RAG)A/B TestingWeights & BiasesDALL-E (Image Generation Model)Machine LearningAgentic AIPrompt EngineeringSemantic Kernel+32 more

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Job description

Location Bangalore

Experience 7–14 Years

Employment Type Full-Time

ABOUT THE ROLE

We are seeking a seasoned AI Engineer to build, fine-tune, and deploy intelligent AI systems at scale. You will

work at the intersection of LLMs, machine learning, and software engineering — developing production-ready AI

features and pipelines that power our core product.

KEY RESPONSIBILITIES

• Design, develop, and deploy AI/ML models and pipelines in production environments

• Implement Retrieval-Augmented Generation (RAG) architectures and agentic AI workflows

• Fine-tune and optimize LLMs for domain-specific use cases using RLHF, LoRA, QLoRA

• Build robust prompt engineering frameworks and evaluation pipelines

• Integrate LLM APIs (OpenAI, Claude, Gemini) and open-source models into product features

• Develop and maintain vector search infrastructure and embedding pipelines

• Collaborate with architects, backend engineers, and product teams on AI feature delivery

• Monitor model performance, conduct A/B testing, and iterate based on metrics

• Implement guardrails, safety layers, and hallucination-mitigation strategies

• Contribute to MLOps practices: model versioning, deployment pipelines, monitoring

KEY SKILLS & REQUIREMENTS

• Strong expertise in Python, with deep knowledge of AI/ML libraries (PyTorch, TensorFlow, HuggingFace

Transformers) • Hands-on experience with LLM APIs and prompt engineering techniques (CoT, few-shot, ReAct) • Experience with RAG systems, embedding models (text-embedding-3, BGE, Cohere), and vector stores

• Knowledge of agentic frameworks: LangChain, LlamaIndex, AutoGen, CrewAI, or Semantic Kernel • Familiarity with fine-tuning techniques: LoRA, QLoRA, PEFT, instruction tuning

• Experience deploying models on cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML) • Understanding of data preprocessing, feature engineering, and model evaluation metrics

• Proficiency with MLOps tools: MLflow, DVC, Weights & Biases, BentoML

• Experience with containerization and orchestration: Docker, Kubernetes

• Strong debugging and experimentation skills with Jupyter, FastAPI, Streamlit

NICE TO HAVE

• Experience with multi-modal models (vision-language models, Whisper, DALL-E) • Published papers or Kaggle/competition achievements

• Exposure to speech AI, computer vision, or NLP specializations

• Knowledge of responsible AI, fairness metrics, and bias

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Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreFree · sign in

Your score for this role already exists

ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

Always free · no credit card · 1 tap with Google

Free · no signup

Get tomorrow's jobs before you have to search

Daily job drops, skill trends and free resources - posted straight to the group. Leave any time.

Join WhatsApp Join Telegram

No spam. Just jobs and resources.

Why people use ASAI

Someone shared one job with you. ASAI keeps finding the rest.

Scored, not searched. Every role ranked against your actual profile.
Alerts as often as hourly. Reach new roles while the pile is still small.
Skill gaps, spelled out. See exactly which requirements you don't meet yet.
Verified jobs, only. Say no to ghost jobs. Your time deserves respect.