# Senior/ Lead AI Engineer

> Weekday AI · Bengaluru, India · Full-time · Posted 2026-09-17

**Salary:** INR 4,200,000–6,000,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟰𝟮𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟲𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟰𝟮-𝟲𝟬 𝗟𝗣𝗔)

Experience: 5+ yrs

Location: Bengaluru

Job Type: Full-time

We are looking for an experienced **Senior AI/ML Engineer – Generative AI** to lead the design, development, and deployment of enterprise-scale AI solutions. The role focuses heavily on **Generative AI, Large Language Models (LLMs), multimodal AI, agentic AI, RAG, and production machine learning systems**.

The ideal candidate will combine strong hands-on engineering expertise with the ability to define AI/ML roadmaps, solve complex technical problems, and guide engineering teams. You will work closely with Business, Product, Engineering, Data Science, and MLOps teams to transform business challenges into scalable, secure, and production-ready AI solutions.

## Requirements

Key Responsibilities

-   Partner with Business, Product, Engineering, Data Science, and MLOps teams to design and deliver enterprise-scale AI solutions.
-   Define and drive the **AI/ML roadmap** for key business and technology problem areas.
-   Lead the design, prototyping, development, and production deployment of **Generative AI and LLM-based applications**.
-   Work with models such as **GPT, Claude, LLaMA, Mistral**, and other foundation and multimodal models.
-   Build scalable **Retrieval-Augmented Generation (RAG)** pipelines, embedding workflows, and retrieval architectures.
-   Design and implement integrations with vector databases such as **FAISS, Pinecone, Weaviate, and Milvus**.
-   Develop and optimise data pipelines supporting AI/ML applications and model workflows.
-   Fine-tune models using approaches such as **LoRA and PEFT** and establish robust evaluation methodologies.
-   Build AI orchestration and agentic workflows using frameworks such as **LangChain and LlamaIndex**.
-   Optimise AI systems for **latency, throughput, cost, scalability, accuracy, and reliability**.
-   Monitor model performance, drift, bias, and production behaviour and implement appropriate corrective measures.
-   Design scalable ML deployment pipelines using cloud-native and containerised environments.
-   Apply appropriate **CI/CD, MLOps, observability, governance, and model lifecycle management** practices.
-   Collaborate with engineering teams to integrate AI capabilities into production applications and platforms.
-   Lead technical debugging, root-cause analysis, performance optimisation, and production issue resolution.
-   Establish best practices for experimentation, evaluation, documentation, security, and production readiness.
-   Mentor and guide engineers while contributing to technical standards and AI/ML engineering practices.
-   Evaluate emerging AI technologies and identify opportunities for their practical application.

What Makes You a Great Fit

-   **5+ years of experience** in AI/ML engineering, with strong hands-on experience delivering **Generative AI solutions into production**.
-   Strong programming expertise in **Python**, with working knowledge of SQL and, where applicable, R.
-   Strong experience with **NumPy, Pandas, Scikit-learn**, and other data science libraries.
-   Hands-on expertise with deep learning frameworks such as **PyTorch, TensorFlow, Keras, MXNet, or Caffe**.
-   Strong understanding of **NLP, LLMs, multimodal AI, and modern Generative AI architectures**.
-   Experience with **Hugging Face, Transformers, SpaCy, NLTK, Gensim, or Spark NLP**.
-   Proven experience building, integrating, evaluating, and fine-tuning **LLMs**.
-   Strong knowledge of **LangChain, LlamaIndex, RAG architectures, embeddings, and vector retrieval**.
-   Hands-on experience with **Pinecone, FAISS, Weaviate, Milvus**, or similar vector databases.
-   Strong understanding of classical machine learning techniques, including regression, SVM, decision trees, random forests, and clustering.
-   Experience with cloud ML platforms such as **AWS SageMaker, Google Vertex AI, or Azure Machine Learning**.
-   Hands-on experience with **Docker, Kubernetes, and cloud-native deployment environments**.
-   Strong knowledge of ML CI/CD, model observability, and governance tools such as **MLflow, Weights & Biases, and LangSmith**.
-   Strong understanding of model evaluation, monitoring, scalability, security, cost optimisation, and production reliability.
-   Excellent analytical and problem-solving skills with the ability to tackle complex AI/ML challenges.
-   Strong technical leadership, communication, stakeholder-management, and mentoring abilities.
-   Bachelor's, Master's, or PhD in **Computer Science, Mathematics, Statistics, Engineering, or a related discipline**from a recognised institution is preferred.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/EF7A520F29/apply)

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