Job ID: INFIT001
Hiring / Immediate joiners
Senior AI Engineer
Locations: Gurgaon (Delhi NCR) or Bangalore (On-site)
Experience Required: 6+ Years
Send Resume: [email protected]/7306892755
Job Title - AI Engineer (Generative AI & Data Products)
About the Role
We are seeking an experienced, product-minded AI Engineer specializing in Generative AI and
Agentic systems to design and build production-grade Data Products. In this role, you will bridge the gap between core backend software engineering and cutting-edge artificial intelligence, transforming complex enterprise data into intelligent, autonomous applications.
The ideal candidate has a strong foundation in data structures, a proven track record of shipping
real-world digital products, and hands-on experience building multi-agent workflows and advanced retrieval systems that solve specific, high-impact business use cases.
Key Responsibilities
• Build GenAI Data Products: Architect and deploy end-to-end data products that leverage
Large Language Models (LLMs) to automate complex workflows, extract insights, and
process large-scale data structures.
• Design Agentic Workflows: Implement autonomous, multi-agent systems capable of
sequential reasoning, tool-calling, and independent decision-making for specific business use cases.
• Advanced Data Ingestion: Design and optimize Retrieval-Augmented Generation (RAG)
pipelines, custom data indexers, and vector database management systems to handle structured and unstructured data.
• Production Engineering: Write clean, production-grade backend APIs and maintain high
availability, security standards, and low latency for deployed AI features.
Required Skills & Qualifications
• Experience: 6+ years of software engineering experience, with a heavy focus on building
and deploying production-scale ML/GenAI systems.
• GenAI & Agentic Expertise: Hands-on experience with LLM orchestration frameworks
(e.g., LangChain, LangGraph, CrewAI) and building practical agent tools.
• Data Product Mindset: Proven experience translating raw data and complex business
rules into user-facing AI applications (e.g., intelligent search, automated compliance,
insight generation).
• Core Tech Stack: Strong proficiency in Python, FastAPI/Flask, SQL, and Vector Databases
(e.g., FAISS, Redis, Pinecone).
• Cloud Infrastructure: Experience deploying applications on cloud platforms (AWS, GCP,
or Azure).
