Top Artificial Intelligence Jobs in Hyderabad

Design and build production AI systems: agentic workflows, multi-agent architectures, RAG, tool-using AI, evaluation and observability pipelines, scalable async execution, failure handling, and standards. Own deployment, monitoring, and mentoring for AI features.

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.

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.

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.

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.

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.

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.

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.

Design and presales of end-to-end AI/HPC infrastructure: size GPU clusters, storage, networking, Kubernetes/container platforms, integrate liquid-cooled racks with facility constraints, validate solutions with OEMs, and support delivery for scalable, operable AI deployments.

Design, develop, and deploy ML models and pipelines; preprocess data and engineer features; implement MLOps (Docker, Kubernetes, CI/CD); collaborate with stakeholders to translate business problems into AI solutions; monitor and optimize model performance and maintain documentation and governance.

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.

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.

Independent full-cycle recruiter managing sourcing, client engagement, offer negotiation, and placements using AI-driven tools. Acts as commercial advisor, provides market insights, and maintains self-directed billing and activity in a results-only, remote environment.

The AI Video Editor / Motion Designer creates AI-driven videos to enhance advertising effectiveness. Responsibilities include video production, concept development, utilizing AI tools, performance analysis, and collaboration with team members.

The Billing Associate will manage outbound insurance tasks, ensure AI performance, and support insurance setups while collaborating on product development.

The AI Engineer will design and develop applications using LLMs, implement multi-agent workflows, optimize RAG pipelines, and contribute to full-stack development, collaborating with teams across regions.

The role involves building AI-powered products, designing reliable LLM-powered systems, and ensuring performance and quality. You'll collaborate in fast-paced environments and own the full product lifecycle.

Lead a hands-on AI-first engineering pod to design, build, and ship agentic orchestration pipelines integrated with Slack, issue trackers, Git and CI/CD. Implement AI-assisted development responsibly, improve CI/CD and quality gates, modernize legacy .NET Core 2.1, mentor engineers, codify playbooks and guardrails, and ensure fintech-grade security and auditability.

Design and build secure, scalable enterprise automation using n8n and related platforms. Implement AI-enabled workflows, API-first and event-driven integrations, CI/CD, observability, governance, and monitoring. Lead architecture and reviews, define standards and templates, mentor teams, and measure impact via automation metrics.

Design and implement graph compiler optimizations (fusion, quantization, tiling) to convert TensorFlow/PyTorch models into IR, improve performance and hardware utilization, collaborate with ML researchers and hardware architects, and lead a team focused on compiler and code-generation improvements.

Design, build, deploy, and maintain AI-native web applications and internal platforms. Use LLMs, autonomous agents, and AI tools to accelerate development. Build secure APIs, databases, CI/CD pipelines, and containerized cloud deployments. Collaborate with stakeholders, conduct code reviews, implement guardrails, and ensure production reliability and security.

Lead enterprise AI strategy, design scalable AI solutions (LLMs, agentic AI, federated learning), evaluate emerging technologies, establish AI governance/Responsible AI, drive XAI adoption, collaborate with stakeholders, and implement advanced generative and orchestration solutions.

Lead the architecture and implementation of a production-grade generative AI media platform. Build reproducible, versioned pipelines, train LoRAs, integrate control techniques (ControlNet, IP-Adapter, inpainting), automate QC against product references, deploy internal tools, and partner with design to own the technical roadmap and enable creative teams.

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.