AI Engineer

***Hybrid in Hyderabad

Immediate - 30 days notice only

Required Skills & Experience

• 4+ years of experience in AI/ML engineering, intelligent automation, or applied AI systems development in an enterprise environment

• 4+ Years of experience in architecting and deploying sophisticated agentic AI systems to enhance reasoning and interaction capabilities in complex workflows

• Hands-on experience with LLM development, OpenAI API usage, custom GPT creation, and RAG implementations. MCP/A2A/ACP familiarity, Agent Evals

• Proficiency in Python with experience in libraries such as PyTorch, TensorFlow, LangChain, or similar.

• Ability to analyze and interpret complex data to improve AI model responses.

• LLM & Agentic Systems: Expert in prompt & context engineering, fine-tuning, and orchestrating multi-agent AI frameworks.

• Strong proficiency in designing and optimizing retrieval-augmented generation pipelines using vector databases and semantic search.

• Experience embedding AI into large-scale enterprise systems, with focus on scalability, compliance, and performance.

• Experience with LLM APIs such as GPTs, vector databases, orchestration frameworks (LangChain, LlamaIndex, etc.)

Nice to Have Skills & Experience

• Proficiency in documenting AI system architectures, processes, and user guides.

Job Description

This AI Engineer & Sr. AI Engineer leads the development, operationalization, and scaling of advanced AI systems and autonomous agents that transform enterprise productivity, and enable intelligent decision-making. This role drives the evolution of enterprise-grade AI platforms and solutions leveraging Large Language Models (LLMs), Agentic AI architectures, and Retrieval-Augmented Generation (RAG) frameworks to deliver measurable impact across business functions. As a senior technical contributor, this individual provides thought leadership in LLM engineering, multi-agent orchestration, and GenAI integration, ensuring alignment with broader innovation roadmap. The Senior Engineer partners with data scientists, and engineering teams to architect, deploy, and continuously refine intelligent systems that scale securely and responsibly across the enterprise.