174 AI Engineer jobs in India available for remote work from home. Apply for positions such as Full-Stack AI Engineer, AI Engineer, Principal, Forward Deployed AI Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will own the AI intelligence behind the Audrey teaching companion, including retrieval, generation, and logic systems. You will also work across the full stack to integrate these AI features into the product while collaborating with engineering teams to ensure reliability and scalability.
Design, build, and deploy advanced AI and Generative AI solutions across healthcare technology platforms. Ensure model performance, scalability, and compliance with healthcare industry regulations like HIPAA.
The Forward Deployed AI Engineer will embed with strategic customers to design, pilot, and operationalize full-stack AI/ML applications and agentic systems. They will also standardize successful patterns into reference architectures and provide technical leadership to drive AI adoption.
Design and build secure, scalable full-stack applications with AI as a core capability. Collaborate with cross-functional teams to deploy and operate these solutions across cloud and hybrid environments.
Develop cutting-edge GenAI solutions and own production rollouts for customer-facing applications. Serve as a trusted technical advisor while collaborating cross-functionally to influence product roadmaps.
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Develop and deploy production-grade AI applications using LLMs and VLMs, including RAG pipelines and multimodal workflows. Optimize inference performance and collaborate with cross-functional teams to transition prototypes into production environments.
You will design, architect, and build scalable AI capabilities and robust SaaS offerings on the Jitterbit platform. You will collaborate with cross-functional teams to ship new features while mentoring other engineers and staying current with emerging AI trends.
Design and implement realistic multi-step scenarios for AI agents to execute on a Linux desktop environment. Write Python scripts to set up these environments and develop automated scoring mechanisms to evaluate agent performance.
You will build and ship full-stack features, including back-end services and agentic AI workflows that power the platform. Additionally, you will contribute to the agent pipeline, design integrations, and maintain production observability to ensure reliable agent behavior.
Design, develop, and deploy scalable Generative AI solutions, including RAG pipelines and Agentic AI workflows. Collaborate with cross-functional teams to integrate LLMs with enterprise data and optimize performance for production environments.
The role involves leading platform modernization efforts and AI-first engineering initiatives. You will be responsible for technical ownership and decision-making within a senior individual contributor capacity.
Design, develop, and deploy scalable Generative AI solutions and LLM-powered applications to solve complex business problems. Partner with stakeholders as a forward deployment engineer to transform prototypes into reliable, production-ready AI systems.
Design, develop, and deploy advanced AI and Generative AI solutions for healthcare platforms while ensuring system integration and performance optimization. Collaborate with cross-functional teams to automate workflows and maintain compliance with healthcare industry regulations.
Lead the engineering delivery of agentic AI solutions and intelligent workflows within the GTM technology stack. Design and optimize scalable enterprise AI architectures, including RAG systems and autonomous agent frameworks.
Architect, develop, and deploy production-grade LLM capabilities within the Kayzen Console. Build backend services and integrations while ensuring high performance, reliability, and observability of AI features.
You will lead the integration of Large Language Models using orchestration frameworks like LiteLLM and direct API connections to Claude. Additionally, you will build scalable backend services with Django and collaborate on frontend features to deliver AI-driven user experiences.
You will architect Generative AI workflows to automate cloud security configuration, drift detection, and remediation. Additionally, you will lead a distributed engineering team in a follow-the-sun model to drive AI enablement across cloud security tooling.
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You will own the production improvement loop for AI agents, including experimentation, evaluation, and monitoring of agent behavior. You will also design and ship targeted improvements to prompting, decision logic, and tool use to ensure reliable business outcomes.
Design, build, and operate core components of an AI-driven search engine including retrieval, ranking, and ingestion infrastructure. Partner with cross-functional teams to integrate modern technologies like LLMs and vector search while mentoring peers.
Design, build, and maintain full-stack features while leveraging AI-assisted tools to streamline revenue processes and platform architecture. You will own features through the full lifecycle, from solution design and development to deployment and production support.
The engineer will translate agentic AI architectures into secure, scalable production deployments using LangChain and LangGraph. They will also embed with customer teams to implement RAG, observability, and evaluation pipelines while ensuring operational readiness.
Design and build autonomous AI agents capable of tool use, memory, and complex multi-step task execution. Develop scalable backend services and observability frameworks to ensure reliability, performance, and quality of AI systems.
Design, develop, and deploy advanced AI and Generative AI solutions across healthcare technology platforms. Collaborate with software engineers to integrate models while ensuring compliance with healthcare regulatory standards like HIPAA.
Design and deploy end-to-end agentic AI systems and LLM-powered applications for enterprise customers. Collaborate with cross-functional teams to integrate predictive ML models and GenAI solutions into production environments.
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The Senior Legal Engineer designs, builds, and deploys AI-powered solutions to automate and transform legal and compliance workflows. This role involves partnering with legal stakeholders to architect scalable applications using LLMs, RAG, and agentic AI frameworks.
The Principal Engineer will own the technical vision and architecture for AI-powered applications, ensuring scalable and secure backend platforms for LLM inference and RAG pipelines. They will also lead technical discovery, establish engineering standards, and partner with cross-functional teams to translate business requirements into durable technical solutions.
The role involves architecting and delivering scalable, secure, and cost-efficient Generative AI applications while leading technical strategy across teams. You will partner with business leaders to translate complex requirements into durable technical designs and establish engineering best practices for AI-native products.
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