Generative AI Solutions Architect

Position Details: Job Title: GenAI Engineer Experience : 4+ years Location Options: Pune, Gurgaon, Noida, Bangalore Skills: A role requiring strong fundamentals, independent reasoning, and technical ownership. Generative AI ConceptsCoding & DebuggingCloud Deployment expertiseSoft skill and Communication Job Description - Working with client stakeholders to gather requirements and translate them into AI/GenAI-based solutions.Designing, developing, and deploying Generative AI models leveraging LLMs (OpenAI, Anthropic, Hugging Face, etc.).Building prompt frameworks, embeddings, and retrieval-augmented generation (RAG) pipelines.Integrating AI models with enterprise workflows, APIs, and client applications.Fine-tuning/customizing foundation models for client-specific use cases.Ensuring model performance, scalability, and cost efficiency.Documenting solution designs, architecture, and providing knowledge transfer to client/internal teams.Applying strong programming skills in Python and working with GenAI frameworks and vector databases (Pinecone, Weaviate, FAISS).Utilizing cloud platforms (AWS, Azure, GCP) for AI/ML deployment along with Git/GitHub and CI/CD workflows.Collaborating with business and functional teams through strong problem-solving and communication skills.Bringing in added expertise with ML Ops practices, data engineering tools (Airflow, DBT, Spark), and Life Sciences/Healthcare applications (preferred). Position Details: Job Title: GenAI Engineer Experience : 4+ years Location Options: Pune, Gurgaon, Noida, Bangalore Skills: A role requiring strong fundamentals, independent reasoning, and technical ownership. Generative AI ConceptsCoding & DebuggingCloud Deployment expertiseSoft skill and Communication Job Description - Working with client stakeholders to gather requirements and translate them into AI/GenAI-based solutions.Designing, developing, and deploying Generative AI models leveraging LLMs (OpenAI, Anthropic, Hugging Face, etc.).Building prompt frameworks, embeddings, and retrieval-augmented generation (RAG) pipelines.Integrating AI models with enterprise workflows, APIs, and client applications.Fine-tuning/customizing foundation models for client-specific use cases.Ensuring model performance, scalability, and cost efficiency.Documenting solution designs, architecture, and providing knowledge transfer to client/internal teams.Applying strong programming skills in Python and working with GenAI frameworks and vector databases (Pinecone, Weaviate, FAISS).Utilizing cloud platforms (AWS, Azure, GCP) for AI/ML deployment along with Git/GitHub and CI/CD workflows.Collaborating with business and functional teams through strong problem-solving and communication skills.Bringing in added expertise with ML Ops practices, data engineering tools (Airflow, DBT, Spark), and Life Sciences/Healthcare applications (preferred).