Senior Gen AI Engineer (Freelancer)
New
W
WeekdayArtificial intelligence
Remote (India)ContractSenior
Salary1,000,000 - 6,500,000 INR per year
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Job Details
- Experience
- 5–13 years of professional experience
- Required Skills
- Artificial IntelligencePrompt EngineeringGenerative AILangChain
Requirements
- Have 5–13 years of experience in software engineering, Artificial Intelligence, Machine Learning, or related technical domains.
- Have hands-on experience developing AI and Generative AI applications.
- Understand Large Language Models (LLMs), foundation models, prompt engineering, model APIs, and AI application architecture.
- Have experience taking AI solutions from prototype to production.
- Be able to work directly with users or customers and rapidly build solutions around their requirements.
- Have strong programming and software engineering fundamentals.
- Have experience designing scalable, reliable, and maintainable AI-powered systems.
- Be able to investigate technical problems independently and deliver solutions in ambiguous, rapidly changing environments.
- LangChain or similar LLM orchestration framework experience is preferred.
- Experience with Agentic AI systems, AI agents, or Retrieval-Augmented Generation (RAG) pipelines is preferred.
- Knowledge of vector databases, embeddings, semantic search, and document processing is preferred.
- Familiarity with AI evaluation, observability, guardrails, monitoring, cloud platforms, Docker, Kubernetes, or CI/CD is preferred.
Responsibilities
- Design 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.
- Partner with customers, product teams, and internal stakeholders to understand challenges and deliver tailored AI solutions.
- Translate ambiguous business problems into AI architectures, prototypes, and production implementations.
- Develop, test, deploy, and optimize AI models and applications across cloud and enterprise environments.
- Integrate foundation models and LLM APIs into scalable applications, considering performance, reliability, security, and cost.
- Evaluate emerging Gen AI technologies, frameworks, and models for business use cases.
- Troubleshoot AI model and application issues and improve quality, latency, scalability, and accuracy.
- Develop reusable components, APIs, tools, and frameworks, and establish evaluation, monitoring, and testing approaches for AI systems.
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