Senior AI/ML Engineer - R01572335

Brillio; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Brillio is seeking an Senior AI/ML Engineer in Bengaluru to design end-to-end AI agent workflows and production-grade RAG pipelines. The role focuses on prompt engineering, embedding strategies, and robust tool integration within scalable systems.

You will collaborate with data scientists to instrument solutions, deploy models in production, and ensure high reliability and traceability. 2–4 years in LLM-based projects and strong Python expertise are essential.

Qualifications

• 2–4 years of experience including at least 2 years in building LLM-based apps, RAG systems or AI agent workflows.
• Strong Python programming skills and hands-on experience with modern LLM tooling.
• Experience designing and evaluating prompt strategies and tool usage for reliable outputs.
• Knowledge of embedding models, vector stores, retrieval re-ranking and context management.
• Experience deploying AI/ML solutions in production and building data pipelines for AI systems.

Responsibilities

• Design end-to-end AI agent workflows from prompts to deployment.
• Build and optimize RAG pipelines with chunking, embeddings and retrieval ranking.
• Iterate on prompts and chain-of-thought approaches for robust outputs.
• Integrate tools with databases, rule engines, and validators in agent flows.
• Implement automated quality checks to catch issues before release.
• Collaborate with data scientists to measure performance and iterate.
• Deploy, monitor and maintain AI solutions in production for reliability.
• Develop feedback loops to convert expert reviews into performance improvements.

Skills

Python

LLM frameworks (LangChain / LlamaIndex

Prompt engineering

RAG architectures

Agent workflows

Production deployment

Data pipelines

Education

Bachelor's degree in Computer Science / Data Science / IT / Statistics

Tools

LangChain

LlamaIndex

Job description

Senior AI/ML Engineer

Job requirements

Experience Range:

2 to 4 years of experience, including at least 2 years specifically focused on developing LLM-based applications, RAG systems, or AI agent workflows

Key Responsibilities:

• Design and build end-to-end AI agent workflows, from initial prompt design through production deployment, ensuring scalable and reliable solutions
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines by implementing chunking strategies, embedding models, retrieval ranking, and context window management for precise information retrieval
• Build and iterate on prompt engineering layers, systematically testing and refining prompts and chain-of-thought strategies to deliver consistent outputs across diverse inputs
• Implement tool orchestration within agent workflows, integrating agents with databases, rule engines, validation systems, and formatting tools for seamless operation
• Establish automated quality checks and validation layers to proactively identify and resolve issues before outputs reach human reviewers
• Collaborate with Data Scientists to instrument solutions for measurement, developing evaluation frameworks and tracking solution performance against defined targets
• Deploy, monitor, and maintain AI/ML solutions in production environments, ensuring reliability, scalability, and robust error handling
• Design and implement feedback loops to capture expert review data and translate it into measurable improvements in agent performance

Required Skills:

• Advanced proficiency in Python
• Hands-on experience with LLM frameworks such as LangChain or LlamaIndex
• Expertise in prompt engineering for systematic testing and iteration
• Deep understanding of RAG architectures including embedding models, vector stores, retrieval strategies, and re-ranking
• Experience building multi-step agent workflows with tool use and branching logic
• Experience deploying and maintaining AI/ML solutions in production environments
• Experience with data pipeline development for feeding AI systems

Preferred Skills:

• Experience with multi-agent orchestration frameworks
• Background in content generation, translation, or document processing solutions
• Familiarity with feedback loops, RLHF, or reward model training
• Knowledge of multi-modal AI systems including voice-to-text, document understanding, and image analysis
• Experience with evaluation frameworks for generative AI and automated scoring
• Experience with LLM cost optimization strategies such as model routing, caching, and prompt compression

Desired Qualifications:

• Bachelor's degree in Computer Science, Data Science, Information Technology, Statistics, or a closely related discipline
• Certification in Machine Learning or Artificial Intelligence (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning - Specialty)
• Certification in LLM engineering or generative AI (e.g., DeepLearning.AI Generative AI with LLMs)