Senior AI Engineer

We're seeking a Senior AI Engineer to architect, build, and scale AI-powered systems that redefine how Yuno operates and innovates.

This role goes beyond building models; it's about designing agentic systems, AI-assisted workflows, and data-driven decision engines that help the company scale faster than headcount.

You will be at the forefront of developing the next generation of autonomous systems that power both customer-facing products and internal operations, from optimizing payment experiences to accelerating development, testing, troubleshooting, and product creation.

Responsibilities:

• Architect, build, and deploy LLM-powered applications that augment and automate key workflows across Yuno, from customer service and new product development to internal agentic workflows that optimize critical company processes.

• Design autonomous AI systems that can execute technical analysis, testing, troubleshooting, and decision-making at scale.

• Develop AI-driven tools that create measurable business impact, improving efficiency, accelerating innovation, and driving revenue growth.

Operational Intelligence & Scalability:

• Identify areas across Yuno where AI can generate efficiency gains, reducing manual work, optimizing processes, and enabling smarter operations.

• Build AI systems that enable Yuno to scale without exponential growth in headcount, thereby creating sustainable productivity and organizational intelligence.

Data & Model Optimization:

• Lead fine-tuning and contextual optimization of AI models using Yuno's proprietary data.

• Continuously refine performance through structured feedback loops, observability metrics, and user interaction data.

• Ensure adherence to privacy, compliance, and ethical AI principles in all model development.

Cross-Functional Collaboration & Innovation:

• Work closely with data, product, and infrastructure teams to define the long-term AI roadmap for Yuno.

• Experiment with emerging AI technologies to identify new capabilities that can drive differentiation and strategic advantage.

• Contribute to a culture of experimentation, rapid iteration, and continuous learning across the AI function.

The skills you need:

• 5+ years of professional experience in AI/ML development, with at least 2 years focused on LLMs, RAG, or agentic systems.

• Strong engineering and product mindset, capable of balancing technical depth with strategic impact.

• Exceptional communication and collaboration skills to work across product, engineering, and data functions.

• Passion for pushing the boundaries of applied AI and creating systems that drive real business transformation.

• Willing to work from the Hyderabad office.

Minimum Qualifications:

• LLMs & RAG: Proven experience designing and deploying systems using models like GPT, Claude, Gemini, or similar, including Retrieval-Augmented Generation (RAG) pipelines and contextual retrieval systems.

• AI Agents & Multi-Agent Systems: Hands-on experience with Crew.ai, LangChain, LangGraph, or similar frameworks to build orchestrated agentic workflows.

• Fine-Tuning & Context Engineering: Expertise in supervised fine-tuning (SFT), LoRA, or custom dataset adaptation for domain-specific tasks.

• Programming & Frameworks: Proficiency in Python, GO, and AI/ML libraries such as PyTorch, TensorFlow, or JAX.

• AI Infrastructure: Experience designing scalable, production-ready AI systems in AWS, GCP, or Azure, with a deep understanding of vector databases, model serving, and inference optimization.

• Observability & Monitoring: Familiarity with LangSmith, LangFuse, or equivalent tools for tracking, debugging, and evaluating LLM performance.

• API Integration: Expertise in integrating AI systems with RESTful APIs and internal platforms to create seamless, usable products.

Preferred Qualifications:

• Experience using LlamaIndex, Hugging Face, or similar open-source frameworks.

• Strong understanding of context optimization, embedding strategies, and knowledge retrieval.

• Familiarity with MLOps, CI/CD pipelines, and production deployment best practices.

• Prior experience in fintech, payments, or other data-intensive and regulated industries.

• Analytical rigor and ability to translate business objectives into measurable AI outcomes.