Artificial Intelligence Engineer

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 efficient, 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 [Confidential Information]