AI Engineer

Job Description Do you love a career where you Experience, Grow & Contribute at the same time, while earning at least 10% above the market? If so, we are excited to have bumped onto you. Learn how we are redefining the meaning of work, and be a part of the team raved by Clients, Job-seekers and Employees. Jobseeker Video Testimonials Employee Glassdoor Reviews If you are a AI Engineer looking for excitement, challenge and stability in your work, then you would be glad to come across this page. We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details. Check if you are up for maximizing your earning/growth potential, leveraging our Disruptive Talent Solution. Role:AI Engineer Location: Hyderabad Experience:6-8 Years Work Mode: Hybrid Type: Contract to Hire Notice Period:Immediate Joiners Requirements Role Summary We are looking for an experienced and hands-on AI Data Engineer to design, develop, and operationalize secure, scalable, production-grade Generative AI, agentic AI, and cloud data solutions. The successful candidate will combine strong AI engineering capabilities—including large language models, prompt engineering, retrieval-augmented generation, vector search, AI agents, and LLMOps—with a solid foundation in Python, advanced SQL, databases, and cloud-based data engineering. The candidate should be also be able to work in establishing data pipelines and engineering—from data ingestion and preparation, to data modeling, deployment and monitoring. AI & Data Engineer · Design, build, and operate secure, scalable, production-grade Generative AI, agentic AI, and cloud data solutions for analytics and reporting. · Develop LLM applications for analytics and reporting using prompt engineering, retrieval-augmented generation (RAG), embeddings, vector search, structured outputs, tool calling, function calling, fine-tuning, and model routing. · Build AI agents that retrieve enterprise data, use approved tools and APIs, coordinate multi-step workflows, and operate within defined guardrails and human oversight. · Integrate foundation models, AI agents, enterprise data platforms, APIs, workflow orchestration tools, document repositories, and reporting applications. · Develop AI capabilities such as natural-language querying, conversational analytics, automated summaries, intelligent recommendations, anomaly detection, narrative reporting, and workflow automation. · Design, develop, and maintain robust ETL/ELT pipelines for structured and unstructured data across data lakes, warehouses, and lake houses. · Design serverless, event-driven, and cost-efficient cloud architectures using a primary cloud platform such as AWS, Azure, or GCP. · Develop data models, data-quality frameworks, validation rules, metadata, lineage, and reusable data products. · Build production-grade services using Python, SQL, APIs, CI/CD, automated testing, infrastructure as code, and…