Senior Staff Engineer, Generative AI

Accountabilities:

• Understand client business use cases and technical requirements and translate them into scalable, practical technical designs.
• Architect and implement end-to-end Generative AI and Agentic AI solutions aligned with functional and non-functional requirements.
• Design and implement RAG architectures, prompt engineering solutions, LLM applications, and AI agents for enterprise use cases.
• Evaluate alternative technical approaches and identify solutions that best address client requirements, scalability, security, maintainability, and performance considerations.
• Define technical guidelines, architecture standards, and benchmarks for non-functional requirements throughout project implementation.
• Create and review architecture, framework, and high-level design documentation to provide clear implementation guidance to development teams.
• Review solutions across extensibility, scalability, security, design patterns, user experience, performance, and other non-functional requirements.
• Select appropriate technologies, frameworks, design patterns, AI services, and infrastructure to deliver robust solutions.
• Develop high-quality, production-ready Python code and remain hands-on throughout solution implementation.
• Build and expose APIs using FastAPI and integrate AI applications with databases through ORM-based approaches.
• Productionize and scale AI systems on Azure or AWS, ensuring enterprise-grade reliability, performance, security, and maintainability.
• Implement and evaluate RAG, LLM, fine-tuning, distillation, and model evaluation approaches.
• Conduct proofs of concept to validate proposed architectures, technologies, and approaches before implementation.
• Analyze and resolve complex technical issues through systematic root-cause analysis and clearly communicate the rationale behind architectural and implementation decisions.
• Translate architecture and design decisions into actionable guidance for developers and engineering teams.
• Collaborate with product and engineering stakeholders to convert business requirements into AI-driven solutions.
• Establish scalable approaches capable of supporting enterprise GenAI workloads and live production environments.
• Contribute to the adoption of emerging AI technologies and practices, including Model Context Protocol (MCP) and open-source GenAI initiatives.

Requirements

• 8+ years of total professional experience in software engineering, AI/ML, data science, or closely related technical disciplines.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• Deep understanding of LLMs and Transformer-based architectures, including models such as GPT, Llama, Claude, Gemini, Qwen, Mistral, and BERT-family models.
• Expert-level prompt engineering skills and strong hands-on experience implementing RAG patterns.
• Strong proficiency in Python and AI/ML technologies and libraries such as LangChain, LlamaIndex, LangGraph, LangSmith, Hugging Face Transformers, Scikit-learn, PyTorch, and TensorFlow.
• Strong experience with fine-tuning, model distillation, model evaluation, and production ML development.
• Strong knowledge of Python, SQL, Pandas, SciPy, and Scikit-learn, with experience in ML model development, validation, deployment, and tuning.
• Hands-on experience implementing anomaly-detection solutions.
• Experience with Snowflake Data Cloud and Snowflake Cortex AI.
• Strong experience with managed AI/ML services on cloud platforms such as Azure Machine Learning Studio or AI Foundry.
• Strong understanding of vector databases and retrieval technologies, including platforms such as Weaviate and Neo4j.
• Knowledge of GenAI evaluation metrics and methodologies, including BLEU, ROUGE, perplexity, semantic similarity, and human evaluation.
• Proven experience architecting and coding scalable GenAI and Agentic AI solutions rather than working solely in an advisory or architecture capacity.
• Ability to write high-quality, production-ready Python with strong testing, maintainability, and engineering practices.
• Proven experience productionizing AI systems on Azure or AWS and scaling AI solutions in live enterprise environments.
• Experience building and exposing APIs with FastAPI and integrating applications with databases using ORM technologies.
• Demonstrated delivery of at least one production Generative AI or Agentic AI solution.
• Familiarity with Model Context Protocol (MCP) is required.
• Contributions to open-source Generative AI projects are an asset.
• Strong architectural thinking, problem-solving, analytical, and root-cause analysis skills.
• Excellent communication skills and the ability to collaborate effectively across product, engineering, development, and client-facing teams.

Benefits

• Opportunity to work on enterprise-scale Generative AI and Agentic AI solutions.
• Hands-on senior technical role combining architecture, software engineering, and AI/ML development.
• Exposure to leading LLM technologies, RAG architectures, AI agents, model evaluation, and modern AI frameworks.
• Opportunity to work across Azure and AWS cloud environments and enterprise AI/ML services.
• Exposure to Snowflake Data Cloud and Snowflake Cortex AI.
• Opportunity to contribute to proofs of concept, architectural standards, technical strategy, and production AI implementations.
• Collaborative environment involving product, engineering, developers, and client stakeholders.
• Opportunity to work with emerging technologies such as MCP and contribute to open-source GenAI initiatives.
• Full-time opportunity based in India.