Top Artificial Intelligence Jobs in Hyderabad

Design and implement AI-enabled ServiceNow solutions across ITSM, FSM, and ITAM. Provide technical leadership and ensure best practices in AI capabilities, facilitate stakeholder workshops, and guide project teams.

The AI Engineer will develop and deploy AI/ML models and solutions, collaborate with teams, and ensure production readiness while addressing complex business problems.

Build and maintain LLM-powered applications and MCP servers, implement tool/function calling and prompt pipelines, rapidly prototype new AI tools, track AI tool releases, and deliver weekly intelligence reports with demos and recommended integrations.

Lead governance and continuous improvement of AI operations reporting, dashboards, and KPIs. Analyze consumption, billing, cost, capacity, and performance data to produce executive and operational reports, detect anomalies, recommend actions, and support forecasting, chargeback, and data governance across AI platforms.

Provide hands-on technical support to customers deploying, operating, and scaling ArangoDB-based AI systems. Diagnose issues, optimize queries and performance, configure deployments across Kubernetes and cloud/on-prem, debug networking/storage, script automations, and document solutions while collaborating with Product and Engineering.

Create original graduate-to-PhD-level problems and rigorous step-by-step solutions in STEM fields, review AI-generated answers to identify reasoning or factual errors, and ensure clarity and verifiability. Work remotely and asynchronously through an online platform after identity verification and an initial assessment.

Design self-contained, realistic software engineering problems for AI agents, configure Docker development environments, write deterministic automated tests, and produce verified reference solutions. Work independently to debug unfamiliar codebases and ensure tasks are solvable and gradable.

Engage with clients to identify AI integration opportunities using Beacon.li's platform, translate requirements into product features, drive roadmap prioritization, collaborate with engineering/design/data science, deliver demos/workshops, and monitor post-deployment performance to ensure client value.

Develop and integrate AI-driven features into web applications. Build responsive, interactive UI components with JavaScript, HTML, and CSS. Work with AI/ML models and APIs, optimize performance for scalability, collaborate with product/design/engineering teams, write clean maintainable code, and communicate progress and challenges to stakeholders and clients.

Manage full sales cycle for Oorwin AI in the US region: prospecting, demos, negotiating contracts, closing deals, and account expansion. Maintain CRM records, collaborate with marketing, product, and customer success, and consistently meet monthly quotas and performance targets.

Lead design, training, and fine-tuning of large-scale ML/DL models (LLMs and generative systems) for drug discovery. Build scalable training pipelines, data pipelines, and production-ready model deployments; collaborate with engineering teams; translate research into applied AI solutions and continuously improve model performance and reproducibility.

Execute fashion design briefs using Raspberry AI to produce flats, tech packs, colorways, prints, mood boards, and concept visuals. Translate creative direction into precise prompts, iterate on feedback, maintain brand-consistent quality, document workflows, flag platform issues, and partner with US Customer Success for intake and delivery under tight turnarounds.

Design and build production LLM-based agent systems, governance knowledge pipelines, hybrid retrieval and evaluation frameworks, and platform infrastructure. Implement behavioral shaping, observability, and constraints to ensure agents align with governance and compliance requirements, collaborating with product and data teams.

The AI Engineer will maintain and enhance AI services on the Sootra platform, optimizing pipelines, managing microservices, and developing feedback systems to improve AI performance.

Build and ship AI-powered features for fashion, beauty, and home using large-scale product, image, and consumer data. Prototype with LLMs, agents, multimodal and CV models, run experiments, measure impact, and take models end-to-end from hypothesis to production while collaborating with product, design, and business teams.

Design and build the core intelligence layer for enterprise AI workflows: document extraction, retrieval, ranking, generation, evaluation pipelines, agentic task execution, and integration into a polished product while prioritizing accuracy, traceability, and human-in-the-loop review.

Build and scale a full-stack Next.js application tracking PRs, CI health, test parity, and benchmarks across AI accelerator open-source projects. Integrate GitHub APIs and webhooks, design PR/metrics schemas, visualize results, and produce technical digests and reports on cross-accelerator parity and performance trends.

Build and maintain Python/FastAPI backend services and React frontends, design and consume REST APIs, work with relational databases, and implement/debug AI-enabled features including vector DBs, embeddings, semantic search, and RAG workflows. Improve existing codebases, collaborate with product and design, participate in testing, deployment, and monitoring, and ensure performance, security, and maintainability.

The AI Tech Lead will design, develop, and implement AI solutions, focusing on LLM and RAG systems, while collaborating with engineers and product managers to innovate and optimize AI workflows.

Lead design, development, and deployment of production-grade AI solutions focused on generative AI and NLP for healthcare. Own model lifecycle, build LLM/RAG workflows, work with clinical and operational data, ensure RAI/compliance, and mentor data science teams while partnering with product, engineering, clinical, and compliance stakeholders.

Design, develop, and deploy ML models and LLM-based applications; implement RAG and vector database pipelines; fine-tune models, optimize inference and scalability; build REST APIs and backend integrations; monitor AI system performance; collaborate cross-functionally and stay current with AI advancements.

Design, develop, and operate AI-powered software systems focused on practical implementation. Build and optimize prompts, create data pipelines, fine-tune/apply RAG, automate LLM workflows/agents, and produce data visualizations from financial datasets for production use.

Design and deliver end-to-end AI architectures for banking: select LLMs and vector stores, integrate with core systems, ensure scalability, availability, security, and regulatory compliance while partnering with engineering, security, and platform teams through deployment.

Build the core AI intelligence for an enterprise compliance workflow product: document extraction, retrieval, RAG, evaluation pipelines, agentic automation, auditable generation, and integration into a polished SaaS product. Focus on reliability, traceability, and making AI useful for operational workflows in manufacturing and supply chains.

Design, develop, and maintain scalable full-stack applications using Node.js and React.js. Build and integrate REST APIs and AWS cloud solutions (including AWS Bedrock exposure). Integrate Generative AI/LLM capabilities into applications and collaborate with cross-functional teams to deliver high-quality software.