AI Engineer
Design, develop, and deploy AI-powered applications using enterprise AI stacks and modern orchestration tools. Collaborate with cross-functional teams to build intelligent agents and ensure alignment with business objectives.
164 AI Engineer jobs in India available for remote work from home. Apply for positions such as AI Engineer, AI Engineer, AI Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design, develop, and deploy AI-powered applications using enterprise AI stacks and modern orchestration tools. Collaborate with cross-functional teams to build intelligent agents and ensure alignment with business objectives.
You will design, develop, and deploy AI-powered applications and intelligent multi-agent systems using enterprise AI stacks. The role involves building proof-of-concepts, implementing RAG architectures, and ensuring observability through CI/CD pipelines.
Design, develop, and deploy AI-powered applications using enterprise AI stacks and modern orchestration tools. Collaborate with cross-functional teams to build intelligent agents and ensure alignment with business objectives.
You will design, develop, and deploy generative AI and LLM-powered services, including intelligent chatbots and workflow automation. Additionally, you will build and optimize end-to-end RAG pipelines and agentic systems to ensure accurate and reliable AI performance.
You will build AI agents, intelligent systems, and automated workflows by taking ideas from prototype to production. The role involves collaborating with stakeholders to experiment with solutions and implement reliable AI systems using Python and FastAPI.
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Architect and build backend services, data pipelines, and orchestration workflows for LLMs and agent-based systems. Collaborate with cross-functional teams to translate complex business requirements into scalable AI platform components.
You will design, deploy, and manage intelligent AI agents and optimize complex RAG pipelines to automate customer tasks. Additionally, you will collaborate with product teams to translate requirements into technical specifications while ensuring robust backend architecture and system health.
You will build and deploy production-grade AI agents, intelligent systems, and automated workflows to solve complex business problems. The role involves collaborating with cross-functional teams to integrate AI solutions with backend services and third-party platforms.
You will build and productionize AI systems, including LLM pipelines, agents, and real-time voice systems. Additionally, you will design evaluation suites and maintain backend infrastructure to ensure reliable, scalable AI products.
Architect and build production-grade agentic systems and a shared AI platform to support internal engineering workflows and product teams. Drive an AI-first culture while ensuring system reliability, safety, and cost-efficiency at enterprise scale.
Design realistic, multi-step coding and technical tasks to evaluate the reasoning and instruction-following capabilities of frontier AI models. Grade model outputs against rubrics, provide structured feedback, and collaborate with the team to improve AI engineering practices.
You will design and build backend services and ML-powered features for an AI-driven search engine. Additionally, you will develop responsive front-end interfaces and maintain data ingestion pipelines to support search functionality.
The AI Engineer will maintain and optimize LLM and VLM-powered services to ensure production stability and high performance. They will also manage microservice architectures, build feedback loops for model evaluation, and collaborate with cross-functional teams to improve AI outputs.
You will build and deploy production-grade AI and agentic workflows while establishing engineering standards for the AI Centre of Excellence. This involves designing reusable component libraries, managing retrieval stacks, and ensuring system reliability through rigorous evaluation and observability.
Lead the architecture and production delivery of enterprise LLM and agentic AI systems for claims, risk, and operational workflows, including RAG, multi-agent coordination, document intelligence, and secure tool integrations. Establish evaluation, observability, governance, and reliability practices while mentoring engineers and translating business objectives into scalable AI capabilities.
You will set the technical direction for AI systems, designing and building production-grade LLM and NLP solutions. Additionally, you will lead engineering efforts, mentor team members, and ensure system trustworthiness through robust evaluation and monitoring.
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Design and build automated marketing workflows by integrating various tools and AI models via APIs and webhooks. Ensure the reliability and maintainability of these systems while translating marketing requirements into technical specifications.
The role involves owning the delivery, model-serving, and observability layers for AI-native platforms across various environments. You will manage CI/CD/CV pipelines, resource governance, and cost attribution to ensure AI workloads are scalable, secure, and economically bounded.
The Product Support Engineer will act as a subject matter expert, managing technical support tickets and troubleshooting complex issues across Netomi's AI platform. They will also collaborate with cross-functional teams to improve internal processes, document knowledge base articles, and assist in client environment setups.
You will serve as the primary escalation point for complex technical issues, managing them from investigation through resolution. Additionally, you will act as a bridge between the Support and Engineering teams to ensure only qualified technical defects are escalated.
You will design, develop, and deploy production-grade AI solutions to create measurable business value across Danaher operating companies. You will collaborate with multidisciplinary teams to industrialize AI and build scalable, reusable AI services and workflows.
Design and own scalable backend services and high-performance APIs for enterprise AI applications. Build and optimize infrastructure for AI agents, RAG pipelines, and enterprise automation workflows.
Design and maintain scalable data pipelines and cloud-based data solutions using Python, SQL, and AWS. Collaborate with product and business teams to build data ingestion, transformation, and analytics solutions for large-scale datasets.
The Senior AI Engineer will build and maintain production-grade AI and agentic workflows, including retrieval systems and orchestration logic. They are responsible for establishing engineering standards, mentoring team members, and creating a reusable component library for internal and partner use.
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You will architect and build LLM-based applications, including copilots, chatbots, and AI agents using RAG and grounded AI systems. Additionally, you will own backend services for AI inference, drive LLMOps practices, and mentor engineers to ensure scalable and responsible AI deployments.
You will own core backend features end-to-end, including data modeling, API design, and the implementation of algorithmic logic. You will collaborate with a distributed team to build scalable, reliable services while shaping technical conventions and patterns.
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