We are seeking an AI Developer with strong hands-on experience in NLP, large language models, and agentic AI systems. The ideal candidate will help build enterprise-grade AI products that automate knowledge work, support decision-making, and integrate intelligently with business systems. Enterprise LLM applications often rely on retrieval, orchestration, monitoring, and security controls, while agentic AI adds multi-step workflow execution across connected tools and systems.
Responsibilities
- Design and develop LLM-powered enterprise features such as knowledge assistants, document intelligence, search, summarization, and workflow automation.
- Build agentic AI workflows that can plan, reason, call tools, and complete multi-step tasks across enterprise systems.
- Work with RAG pipelines, prompt engineering, evaluation, fine-tuning, and model orchestration.
- Integrate AI solutions with internal platforms, APIs, databases, CRMs, ERPs, and document repositories.
- Develop safeguards for hallucination reduction, prompt injection resistance, logging, auditability, and access control.
- Collaborate with product, backend, data, and DevOps teams to move models from prototype to production.
- Monitor model quality, latency, cost, and user feedback to continuously improve system performance.
Required Skills
- Strong Python programming skills.
- Solid understanding of NLP, transformer architectures, embeddings, and vector search.
- Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or similar orchestration tools.
- Experience building RAG-based systems and evaluating LLM outputs.
- Familiarity with API development, model deployment, and cloud environments.
- Understanding of prompt engineering, function calling, agents, and tool use.
- Experience with Git, debugging, testing, and production support.
Preferred Skills
- Experience with enterprise AI use cases such as internal copilots, document automation, enterprise search, or workflow agents.
- Familiarity with LLM observability, prompt/version tracking, and evaluation platforms.
- Knowledge of secure deployment practices, role-based access, and compliance requirements.
- Exposure to Docker, Kubernetes, CI/CD, and MLOps practices.
- Experience with open-source or commercial LLMs and model comparison workflows.
Pay: ₹33,333.60 - ₹49,999.68 per month
Benefits:
- Flexible schedule
- Life insurance
- Paid sick time
- Paid time off
- Provident Fund
- Work from home
Work Location: In person
