AI Engineer - LLM

Magnet HR Consulting Services; Bengaluru; On-site; INR 2,000,000 - 3,800,000; Full time

Job summary

Magnet HR Consulting Services in Bengaluru seeks a senior AI/ML engineer to join our team delivering Generative AI solutions. You will work at the intersection of Generative AI, RAG, NLP and software engineering to design scalable systems and production‑grade AI services.

We expect 5+ years in software engineering, 3+ years with ML/NLP/AI, and 1.5+ years building LLM or Generative AI apps, with strong Python and modern ML frameworks for impactful delivery.

Qualifications

• 5+ years of professional software engineering experience.
• Approximately 3+ years of experience working with Machine Learning, NLP, or related AI technologies.
• At least 1.5+ years of hands‑on experience building LLM or Generative AI applications.
• Strong, production‑grade programming skills in Python.
• Experience designing and implementing scalable software systems.
• A strong understanding of modern LLM and Generative AI application architecture.
• Experience building or contributing to production‑grade RAG systems.
• The ability to take ownership of technical solutions and contribute to architectural decisions.

Responsibilities

• Develop and deliver AI applications solving real business problems.
• Collaborate with engineers to design scalable, production‑ready systems.
• Leverage RAG and NLP techniques to improve search, retrieval, and response quality.
• Evaluate and iterate on model performance, latency, and reliability.
• Build reusable AI services and contribute to architecture decisions.

Skills

Software engineering

Machine Learning

NLP

LLM development

Python

System design

LLM architecture

RAG systems

Tools

LangChain

PyTorch

TensorFlow

Kubernetes

MLOps

Job description

You should have :

• 5+ years of professional experience in software engineering.
• Approximately 3+ years of experience working with Machine Learning, NLP, or related AI technologies.
• At least 1.5+ years of hands‑on experience building LLM or Generative AI applications.
• Strong, production‑grade programming skills in Python.
• Experience designing and implementing scalable software systems.
• A strong understanding of modern LLM and Generative AI application architecture.
• Experience building or contributing to production‑grade RAG systems.
• The ability to take ownership of technical solutions and contribute to architectural decisions.

Technical Skills :

Generative AI & LLMs :

• Hands‑on experience with one or more of the following :

1. GPT
2. Claude
3. Gemini
4. Llama
5. Other Large Language Models

Experience with :

1. Prompt engineering
2. Context engineering
3. Embeddings
4. Inference optimisation
5. LLM application development
6. Evaluation and response quality

RAG & Search :

• Experience with :

1. Retrieval‑Augmented Generation
2. Document ingestion and preprocessing
3. Chunking strategies
4. Vector search
5. Semantic retrieval
6. Response relevance and evaluation

What Will Make You Stand Out :

• We would be particularly interested in candidates with experience in:

1. Building agentic AI or autonomous workflows.
2. Tool-based reasoning and AI orchestration.
3. LangChain, Google ADK, LangGraph, or similar frameworks.
4. PyTorch or TensorFlow.
5. MLOps platforms and practices.
6. Kubernetes and cloud-native deployment.
7. Production AI monitoring and evaluation.
8. Enterprise search or large‑scale document processing.
9. Financial Services, Banking, BFSI, or Capital Markets.
10. Working within large, complex, or highly regulated enterprise environments.

You will be working at the intersection of :

• Generative AI + RAG + NLP + Agentic AI + Software Engineering

You will have the opportunity to :

• Build AI applications that solve real business problems.
• Work with some of the most advanced LLM technologies available.
• Design systems capable of searching and understanding massive enterprise knowledge bases.
• Gain hands‑on exposure to emerging agent‑based architectures.
• Work on challenging problems involving retrieval accuracy, scale, relevance, and performance.
• Build reusable AI services and production‑ready applications.
• Collaborate with experienced engineers and AI specialists.
• Help shape the future of AI adoption within a global financial services organisation. .