About this Senior AI/ML Engineer - R01571454 role at Brillio
Brillio · Onsite · Gurgaon, Haryana, India
Senior AI/ML Engineer
Job requirements
Experience Range:
2–4 years of experience, including at least 2 years specifically building LLM-based applications, RAG systems, or AI agent workflowsKey Responsibilities:
Design and build end-to-end AI agent workflows, from initial prompt design through production deployment, ensuring scalable and robust solutionsDevelop and optimize Retrieval-Augmented Generation (RAG) pipelines, including chunking strategies, embedding models, retrieval ranking, and context window management to maximize information accuracy and retrieval efficiencyBuild and systematically iterate on prompt engineering layers, testing and refining prompts and chain-of-thought strategies to achieve consistent, high-quality outputs across diverse inputsImplement tool orchestration within agent workflows by integrating agents with databases, rule engines, validation systems, and formatting tools to automate complex tasksEstablish automated quality checks and validation layers to proactively catch issues and ensure high output reliability before human reviewInstrument solutions for measurement, collaborating with data scientists to develop evaluation frameworks and track solution performance against defined targetsDeploy and maintain AI/ML solutions in production environments, focusing on reliability, monitoring, and edge case handlingDesign and implement feedback loops that capture expert review data and translate it into measurable improvements in agent performanceRequired Skills:
Advanced proficiency in PythonHands-on experience with LLM frameworks such as LangChain, LlamaIndex, or similarExpertise in prompt engineering and systematic prompt testingDeep understanding of RAG architectures, including embedding models, vector stores, retrieval strategies, and re-rankingExperience building multi-step agent workflows with tool use, branching logic, and robust error handlingExperience with production deployment and monitoring of AI/ML solutionsExperience with data pipeline tools and frameworks (KubeFlow, BentoML, Great Expectations, Evidently AI)Preferred Skills:
Experience with multi-agent orchestration frameworksBackground in content generation, translation, or document processing solutionsFamiliarity with fine-tuning LLMs or training reward modelsExperience implementing feedback loops or RLHF mechanismsExpertise in LLM cost optimization strategies such as model routing, caching, and prompt compressionExperience with multi-modal AI systems including voice-to-text, document understanding, and image analysisExperience with evaluation frameworks for generative AI, including automated scoring and human evaluation protocolsDesired Qualifications:
Bachelor's degree in Computer Science, Data Science, Information Technology, or a closely related disciplineCertification in Machine Learning or Artificial Intelligence (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning Specialty)Certification in LLM or generative AI technologies (e.g., OpenAI Certified Engineer, Hugging Face Certified AI Practitioner)
