Top Artificial Intelligence Jobs in Hyderabad

Lead design and implementation of enterprise-scale generative AI and agentic systems. Architect multi-agent orchestration, RAG and inference pipelines, fine-tuning/quantization strategies, integrations (APIs, webhooks, connectors), and secure data/model management. Optimize deployments across cloud, edge, and on-premises while establishing evaluation, selection, and lifecycle practices.

Gather and analyze stakeholder requirements and translate them into ServiceNow AI solutions (Virtual Agent, Predictive Intelligence, Now Assist). Collaborate with technical teams to implement AI-driven automation and agentic solutions, optimize workflows, monitor system performance, train users, and drive adoption while ensuring clear communication between business and technical stakeholders.

Lead development of GenAI and LLM-powered applications using Python, LangChain/LangGraph and FastAPI. Design scalable cloud-ready microservices, integrate LLMs (AWS Bedrock/OpenAI), implement prompt engineering, and build interactive frontends with Angular/JavaScript. Ensure AWS-based deployment and database integration (SQL/NoSQL).

Lead architecture, design, and governance for enterprise-scale AI solutions on the ServiceNow platform, implementing Now Assist, Virtual Agent, Agentic AI, predictive and task intelligence, integrations, and AI governance frameworks.

Design and lead enterprise-grade AI and Gen-AI integrations using the MCP (Model-Context-Prompt) framework. Architect LLM integrations, define prompt engineering and context strategies, evaluate models, design scalable secure solutions, oversee deployment/monitoring/optimization, mentor development teams, translate business needs into technical designs, and provide night-shift production support.

Build and operate backend services and infrastructure for LLM- and voice-driven healthcare applications. Implement APIs, productionize LLM workflows, deploy cloud containerized services, and monitor performance and reliability end-to-end.

Develop, deploy, and scale AI/ML and generative AI solutions for a fintech platform. Design data models and pipelines, build agentic frameworks, integrate OCR and vector DBs, implement RAG, and champion MLOps and cloud deployment practices while mentoring teammates.

Design and build a production multi-agent harness and MCP integrations that operate across ERPs, CRMs, and business tools. Own end-to-end production concerns (reliability, observability, permissions, safe workflow execution), scope the product, make architecture decisions, and ship features working closely with CTO, product, engineering, and design. Stay current with agent frameworks and use tools like Claude Code in development.

Build and deploy autonomous AI agents and internal copilots that research, enrich, reason, and execute GTM workflows. Implement RAG with embeddings and vector DBs, integrate agents with HubSpot and internal systems, automate data pipelines and scraping, and own agent systems end-to-end from prototype to production.

Design, implement, and maintain production AI/ML solutions. Deploy scalable, secure models and software, collaborate with data scientists, ensure reliability and incorporate new frameworks and technologies.