AI Engineer - India
Pulsora, Inc. (company site, opens in a new tab)5+ yrsHyderabadOn-siteDirect career pageEst. 25–40 LPA
Posted on 10 Sept
Reach people at Pulsora, Inc.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Pulsora, Inc. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, develop, and deploy production-grade AI applications focused on Large Language Models (LLMs), including multi-agent workflows and Retrieval Augmented Generation (RAG) systems.
- Lead efforts in LLM fine-tuning, prompt engineering, and use AI-powered coding tools to build and integrate full-stack software (frontend and backend).
- Collaborate closely with US-based teams and manage integration of Python-based AI modules with Java services using multi-threading where applicable.
Minimum Requirements
- Undergraduate degree in Computer Science or similar engineering discipline.
- 5+ years of professional software development experience, including minimum 2 years with AI/ML development focused on Large Language Models.
- Proficient in Python and experienced with major LLM APIs, LangChain/LangGraph frameworks, RAG architectures, vector databases, and prompt engineering.
- Willingness to work overlapping hours with US time zones; Hybrid work with 2-3 days/week office presence applicable only for certain global locations (not India).
Ideal Candidate Profile
- Experienced AI/ML engineer with deep practical expertise specifically in LLM integration, fine-tuning, and building agentic workflows using LangChain/LangGraph.
- Comfortable owning end-to-end product development including frontend and backend, leveraging AI coding assistants for efficient delivery.
- Collaborates effectively across distributed teams and handles ambiguity to build production-ready AI-first software solutions.