Sr. AI Engineer

MyNaksh; Bengaluru; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

MyNaksh is seeking a Senior AI Engineer to tackle frontier AI challenges at the intersection of personalization and human relationships. You will build production-grade ML/AI systems, develop LLMs, RAG, and agentic workflows, and work on memory, recommendations, and user intelligence.

You will collaborate with product and backend teams to ship impactful features at scale while focusing on quality, latency, and cost optimization.

Qualifications

• 3-5 years in ML, applied ML, NLP, or GenAI engineering.
• Strong Python and software engineering fundamentals.
• Hands-on experience with LLMs, RAG, embeddings, vector search, or conversational AI.
• Experience deploying ML/AI systems to production.
• Strong understanding of ML fundamentals, evaluation, APIs, system design, scalability, and cloud.
• Ability to own problems end-to-end: design, build, evaluate, and produce.

Responsibilities

• Build and own production-grade ML/AI systems end-to-end.
• Develop LLM, RAG, conversational AI, and agentic workflows.
• Work on personalization, memory, recommendations, and user intelligence.
• Build LLM orchestration, evaluation, and optimization systems for quality, latency, and cost.
• Combine structured astrology intelligence with ML, retrieval, and LLM reasoning.
• Work closely with product, backend, and other teams to ship impactful features at scale.

Skills

ML experience

Python

LLMs/RAG

Production ML

End-to-end ownership

System design/cloud

Tools

LangChain/LangGraph

Vector databases

Hugging Face

Open-source LLMs

MLOps

Job description

We are Senior AI Engineers; this means working on some of the hardest problems at the intersection of AI, personalization, and human relationships: building models that understand users deeply, learn from long-term interactions, develop persistent context, and deliver increasingly personalized conversations at scale. This is frontier AI work figuring out how AI learns to know a person and how that person can trust our AI more than anyone else in their world.

Responsibilities:

• Build and own production-grade ML/AI systems end-to-to-end.
• Develop LLM, RAG, conversational AI, and agentic workflows.
• Work on personalization, memory, recommendations, and user intelligence.
• Build LLM orchestration, evaluation, and optimization systems for quality, latency, and cost.
• Combine structured astrology intelligence with ML, retrieval, and LLM reasoning.
• Work closely with product, backend, and other teams to ship impactful features at scale.

Requirements:

• 3-5 years in ML, applied ML, NLP, or GenAI engineering.
• Strong Python and software engineering fundamentals.
• Hands-on experience with LLMs, RAG, embeddings, vector search, or conversational AI.
• Experience deploying ML/AI systems to production.
• Strong understanding of ML fundamentals, evaluation, APIs, system design, scalability, and cloud.
• Ability to own problems end-to-end: design, build, evaluate, and produce.

Good to Have:

• Experience with LangChain/LangGraph.
• Familiarity with vector databases.
• Work with Hugging Face or open-source LLMs.
• MLOps and LLM evaluation expertise.
• Background in recommendation systems.
• Experience with Indic or multilingual NLP.