AI Developer
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. Key Responsibilities Responsibilities and duties:
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: ₹41,598.47 - ₹50,010.79 per month
Benefits:
- Cell phone reimbursement
- Flexible schedule
- Health insurance
- Paid sick time
- Paid time off
- Provident Fund
- Work from home
Work Location: In person
