Senior AI/ML Engineer - R01572335

Lever, Inc.; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Lever, Inc. is seeking a Senior AI/ML Engineer in Bengaluru, India to design and deploy end-to-end AI agent workflows, including RAG-based pipelines and prompt engineering.

The role emphasizes production-ready systems, evaluation, and continuous improvement across cross-functional teams. You will work with Data Scientists to instrument solutions, optimize embeddings and vector stores, and ensure scalable, reliable AI deployments in production environments.

Qualifications

• 2–4 years of experience with at least 2 years in LLM-based apps, RAG systems or AI agent workflows
• Strong Python proficiency and experience with LLM frameworks
• Experience building end-to-end AI agent workflows
• Production deployment experience in AI/ML projects

Responsibilities

• Design and build end-to-end AI agent workflows from prompts to production
• Develop and optimize RAG pipelines with chunking, embeddings, retrieval ranking and context window management
• Iterate on prompt engineering layers and chain-of-thought strategies
• Implement tool orchestration within agent workflows integrating databases, rule engines and formatting tools
• Establish automated quality checks and validation layers before outputs reach humans
• Collaborate with Data Scientists to instrument solutions and track performance
• Deploy, monitor, and maintain AI/ML solutions in production with reliability and error handling
• Design feedback loops to capture expert review data and translate into improvements

Skills

Python

LangChain

LlamaIndex

Prompt engineering

RAG architectures

Embeddings

Vector stores

Agent workflows

Production deployment

Data pipelines

Education

Bachelor's degree in CS/DS

TensorFlow Developer Certificate

AWS Certified Machine Learning – Specialty

LLM/Generative AI certification

Tools

LangChain

LlamaIndex

Vector stores

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)