Senior AI/ML Engineer

Ciklum is looking for a Senior AI/ML Engineer to join our team full-time in India.

We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.

About the role:

As a Senior AI/ML Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.

We are seeking a highly skilled Senior AI/ML Engineer to design, optimize, and validate enterprise-grade AI solutions powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and advanced NLP techniques. The ideal candidate will be responsible for leading technical audits, improving retrieval performance, building automated evaluation frameworks, and mentoring engineering teams to deliver scalable and reliable AI products.

Responsibilities:

• AI/ML Engineering & Solution Development
• Design, develop, and deploy production-grade AI/ML applications using Python
• Translate solution blueprints and architectural designs into scalable, maintainable code
• Lead technical reviews and ensure adherence to engineering best practices
• Drive continuous improvements in model performance, scalability, and reliability
• Retrieval-Augmented Generation (RAG) & Search Optimization
• Lead technical audits of RAG pipelines and retrieval architectures
• Instrument and monitor KPIs across pgvector-based retrieval systems
• Optimize hybrid retrieval strategies combining BM25, vector databases, and semantic search techniques
• Analyze retrieval performance and implement enhancements to improve relevance, accuracy, and user experience
• AI Quality Assurance & Evaluation
• Build automated evaluation frameworks using RAGAS and other LLM assessment methodologies
• Develop Python-based validation harnesses to measure faithfulness, relevance, answer correctness, and retrieval effectiveness
• Establish AI quality scorecards and performance benchmarks
• Integrate evaluation metrics into CI/CD pipelines and Azure DevOps quality gates to ensure release readiness.
• Leadership & Collaboration
• Provide technical leadership and day-to-day guidance to mid-level engineers
• Conduct code reviews and mentor team members on AI/ML engineering best practices
• Collaborate with product managers, architects, and stakeholders to define technical roadmaps and delivery plans
• Drive continuous improvement initiatives across AI engineering and testing practices.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field
• 6+ years of experience in Machine Learning, NLP, Generative AI, or related domains
• Strong proficiency in Python and modern software engineering practices
• Hands-on experience with Retrieval-Augmented Generation (RAG) architectures
• Deep understanding of hybrid retrieval techniques, including BM25, vector databases, and semantic search
• Experience with pgvector, vector databases, embeddings, and retrieval optimization
• Expertise in LLM evaluation frameworks such as RAGAS
• Experience building automated testing and validation frameworks for AI applications
• Strong understanding of Azure DevOps, CI/CD pipelines, and quality gate implementation
• Proven experience conducting code reviews and mentoring engineering teams

Desirable:

• Experience with Azure OpenAI, OpenAI, Anthropic, or other enterprise LLM platforms
• Knowledge of LangChain, LlamaIndex, Semantic Kernel, or similar AI orchestration frameworks
• Experience working with PostgreSQL, pgvector, and large-scale data pipelines
• Familiarity with observability, monitoring, and AI governance frameworks
• Experience deploying AI solutions in cloud environments such as Azure, AWS, or GCP

What`s in it for you?

• Strong community: Work alongside top professionals in a friendly, open-door environment
• Growth focus: Take on large-scale projects with a global impact and expand your expertise
• Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications
• Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge techno…