Multi-Agent Generative AI Build
Budget: ₹400 – ₹750 INR
Primary (Required) Skills
AI / ML Leadership: 8-12+ years of software engineering experience with senior-level ownership in Generative AI systems, particularly NLP and LLM-based solutions.
Generative AI: Hands-on experience building GenAI solutions, including prompt engineering, RAG architectures, and model adaptation/fine-tuning.
Agentic AI: Proven experience designing and building multi-agent systems capable of reasoning and planning using frameworks such as Lang Chain, Lang Graph, Crew AI, or similar.
Programming & ML Foundations: Strong Python expertise with hands-on experience in AI/ML libraries such as Py Torch, TensorFlow, and Scikit-learn.
Model & Platform Versatility: Experience working with open-source LLMs (e.g., LLaMA, Mistral) and proprietary platforms/APIs (e.g., OpenAI GPT, Google Gemini, Azure OpenAI).
Cloud AI Platforms: Experience with AI/ML services on major cloud platforms such as Vertex AI, SageMaker, or Azure ML.
Preferred Skills
Experience building scalable cloud-native systems using Docker, serverless architectures, and managed cloud services.
Strong API and backend engineering experience.
Working knowledge of SQL (e.g., PostgreSQL) and NoSQL (e.g., DynamoDB) databases.
Experience mentoring engineers and operating in agile, fast-changing environments
AI / ML Leadership: 8-12+ years of software engineering experience with senior-level ownership in Generative AI systems, particularly NLP and LLM-based solutions.
Generative AI: Hands-on experience building GenAI solutions, including prompt engineering, RAG architectures, and model adaptation/fine-tuning.
Agentic AI: Proven experience designing and building multi-agent systems capable of reasoning and planning using frameworks such as Lang Chain, Lang Graph, Crew AI, or similar.
Programming & ML Foundations: Strong Python expertise with hands-on experience in AI/ML libraries such as Py Torch, TensorFlow, and Scikit-learn.
Model & Platform Versatility: Experience working with open-source LLMs (e.g., LLaMA, Mistral) and proprietary platforms/APIs (e.g., OpenAI GPT, Google Gemini, Azure OpenAI).
Cloud AI Platforms: Experience with AI/ML services on major cloud platforms such as Vertex AI, SageMaker, or Azure ML.
Preferred Skills
Experience building scalable cloud-native systems using Docker, serverless architectures, and managed cloud services.
Strong API and backend engineering experience.
Working knowledge of SQL (e.g., PostgreSQL) and NoSQL (e.g., DynamoDB) databases.
Experience mentoring engineers and operating in agile, fast-changing environments