NOTE: Candidates with 7+ years experience only apply, based in Pune and open to work from office with serving NP or below 60 days NP. Position: Senior AI Engineer

Location:
Viman Nagar, Pune, MH Hybrid
- (3 Work from office) Start Date: ASAP/immediate joiner
- 30 days Shift Time: 4:30 pm to 1:30 am IST Note: Candidates with 5+ yrs exp and above, and currently staying in Pune are considered only. Job Overview We are looking for a capable and agile Senior AI Engineer to join our team and accelerate our AI-based developments. In this role, you will be responsible for the hands-on coding and delivery of AI models and generative AI agentic systems. We need a developer with strong backend foundations who can learn the Intuit AI ecosystem
- AI Workbench, quickly and translate business needs into production-ready capabilities. You will embrace a modern, AI-native development workflow vibe coding using tools like Cursor and Windsurf to rapidly prototype and deliver robust solutions. Responsibilities ● Utilize next-generation AI coding assistants (Cursor, Windsurf) to accelerate the software development lifecycle, moving rapidly from ideation to production deployment ● Design and build AI agents and co-pilots that utilize Model Context Protocol (MCP) servers and tool-use architectures to automate complex workflows. ● Develop and maintain scalable Retrieval-Augmented Generation (RAG) pipelines and semantic search systems to provide high-quality grounding for AI models. ● Build backend services with AI at their core using Java and Python, ensuring scalability for millions of users and requests daily. ● Implement end-to-end features including prompt engineering, context design, fallback logic, and feature-level configuration. ● Discover,



clean, and prepare data sources to refine data pipelines for model training, fine-tuning, and robust evaluation. ● Integrate AI systems with enterprise data sources, APIs, and internal platforms while maintaining strict security and privacy standards. ● Collaborate side-by-side with product managers, data scientists, and backend engineers to define success criteria and align model metrics with business goals. ● Create proofs-of-concept to explore new agent capabilities and frameworks, then harden successful ideas for production use. ● Design for reliability, observability, and cost efficiency in AI-powered systems operating at an enterprise scale. Experience ● 5+ years of industry experience in software engineering. ● 2+ years of specific experience bringing Agentic AI models, LLM applications, RAG & machine learning systems to production. ● Bachelors or Masters in Computer Science, Applied Math, Statistics, or equivalent practical experience. Required Technical Skills ● Demonstrate expert proficiency in Python and Java, with the ability to manually architect, debug, and optimize complex backend services and distributed systems without reliance on external assistants. ● Exhibit proficiency with AI-assisted coding tools (Cursor, Windsurf) to enhance coding velocity and quality (Note: External requirement).



● Possess deep knowledge of Computer Science Fundamentals including data structures, algorithms, performance complexity, and memory tuning to write productive, production-ready code ● Possess experience building agentic systems, multi-agent orchestration, or systems utilizing Model Context Protocol (MCP). ● Maintain deep knowledge of Large Language Models (LLMs), prompt lifecycle management, and fine-tuning techniques such as LoRA and QLoRA. ● Demonstrate implementation experience with Retrieval-Augmented Generation (RAG), vector databases, and semantic search. ● Apply knowledge of data query and data processing tools (i.e., SQL) and familiarity with processing platforms such as Pandas, NumPy, and Spark. ● Foundational AI Skills (Basic & Adopting) ● ML Fundamentals: Solid understanding of machine learning principles (training, validation) and statistical modelling techniques (classification, regression). ● Data Handling: Experience with data processing platforms (e.g., Pandas, NumPy, Spark) and SQL. ● Software Engineering Best Practices: Strong grasp of version control (Git), software design patterns, and writing clean, production-ready code. ● Bias for Action: Ability to operate in ambiguity and deliver practical AI solutions that drive measurable business impact. ● Rapid Ecosystem Adoption: Demonstrated ability to pick up new internal tools, cloud technologies (AWS), and AI infrastructure components quickly. ● Production Mindset: Understanding of AI observability, reliability, and cost-efficiency when operating at scale If you are interested, please do share your updated resume to [email protected]

📌 Artificial Intelligence Engineer (India)
🏢 Aptino
📍 India