Senior Gen AI Engineer (Freelancer)
New
J
JobgetherArtificial Intelligence
Fully remote within IndiaContractSenior
Salary1,000,000 - 6,500,000 INR per year
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Job Details
- Experience
- 5–13 years
- Required Skills
- DockerKubernetesMachine LearningCI/CDPrompt EngineeringLLMGenerative AILangChain
Requirements
- 5–13 years of professional experience in software engineering, Artificial Intelligence, Machine Learning, or related technical disciplines.
- Strong hands-on experience developing AI and Generative AI applications with a track record of moving from prototype to production.
- Solid understanding of Large Language Models (LLMs), foundation models, prompt engineering, and model APIs.
- Strong software engineering and programming fundamentals for building scalable and reliable systems.
- Demonstrated ability to work as a Forward Deployment Engineer engaging directly with users.
- Experience with LangChain or similar LLM orchestration frameworks is a plus.
- Experience building Agentic AI systems, autonomous workflows, or AI agents is highly desirable.
- Hands-on experience with Retrieval-Augmented Generation (RAG), vector databases, and semantic search.
- Familiarity with AI evaluation frameworks, guardrails, and LLM monitoring.
- Experience with cloud platforms and deployment practices including Docker, Kubernetes, and CI/CD.
Responsibilities
- Design, develop, and implement scalable AI and Generative AI solutions aligned with business and product requirements.
- Build and productionize LLM-powered applications, intelligent automation systems, and AI-driven workflows.
- Operate with a Forward Deployment Engineering mindset, partnering directly with customers and stakeholders to deliver tailored solutions.
- Translate ambiguous business problems into practical AI architectures and production-ready implementations.
- Develop, test, deploy, and optimize AI models and applications across cloud and enterprise environments.
- Integrate foundation models and LLM APIs while balancing performance, reliability, and security.
- Develop reusable components and frameworks to accelerate AI application development.
- Establish evaluation, testing, monitoring, and observability practices for AI systems.
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