AI/ML Solution Architect (GenAI Specialist)

• Collaborate with sales teams to understand customer requirements and provide expert guidance on ML/Generative AI solutions across a wide range of use cases: content generation, document automation, chatbots, virtual assistants, summarization, search, personalization, and more.

• Evaluate and integrate open-source LLMs (e.g., LLaMA, Mistral, Falcon), commercial APIs (e.g., GPT-4, Claude, Gemini), and cloud-native GenAI platforms (e.g., AWS Bedrock, Azure OpenAI).

• Design and deliver compelling Solution and SoW and demonstrations of our Generative AI offerings to both technical and non-technical audiences.

• Design Retrieval-Augmented Generation (RAG), prompt engineering strategies, vector database integrations, and model fine-tuning where required.

• Translate business objectives into technical roadmaps, collaborating closely with product managers, engineers, and data scientists.

• Create prototypes and proof-of-concepts (PoCs) to validate solution feasibility and performance.

• Provide technical mentorship, best practices, and governance guidance across teams and clients.

• Educational Background: Master’s/Bachelor’s degree in computer science, Engineering, or a related field. (e.g., BCA, MCA, B.Tech/B.E, M.Tech/ME)

• 3-5 years of experience in AI/ML development/solutioning, with at least 1-2 years in Generative AI/NLP applications.

• Strong command of transformers, LLMs, embeddings, and NLP methods.

• Proficiency with LangChain, LlamaIndex, Hugging Face Transformers, and cloud AI tools (SageMaker, Bedrock, Azure OpenAI, Vertex AI).

• Experience with vector databases like FAISS, Pinecone, or Weaviate.

• Familiarity with MLOps practices, including model deployment, monitoring, and retraining pipelines.

• Skilled in Python, with working knowledge of APIs, Docker, CI/CD, and RESTful services.

• Experience in building solutions in both agile startup environments and structured enterprise settings.

• Certifications (e.g., AWS Machine Learning Specialty, Azure AI Engineer).

• Exposure to multimodal AI (text, image, audio/video) and Agentic AI.

• Experience with data privacy, responsible AI, and model interpretability frameworks.

• Familiarity with enterprise security, scalability, and governance standards.

• Entrepreneurial mindset with a bias for action and rapid prototyping.

• Strong communication and stakeholder management skills.

• Comfortable navigating ambiguity in startups and structured processes in enterprises.

• Team player with a passion for continuous learning and AI innovation.

• The flexibility and creativity of a startup-style team with the impact and stability of enterprise-scale work.

• Opportunities to work with cutting-edge GenAI tools and frameworks.

• Collaborative environment with cross-functional tech and business teams.

• Career growth in a high-demand, high-impact AI/ML domain.

Rapyder