Position: <\/b>AI\/ML Solution Architect <\/b>(GenAI Specialist)
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<\/span><\/span><\/span>Team: <\/b>ML\/GenAI Team
<\/p> <\/span><\/span><\/span>Number of Resources Needed: <\/b>1
<\/p> <\/span><\/span><\/span>Years of Experience: <\/b>3\-5 Years
<\/p> <\/span><\/span><\/span>Educational Background: <\/b>BCA, MCA, B.Tech\/B.E, M.Tech\/ME
<\/p> <\/span><\/span><\/span>Type: <\/b>Full\-time
<\/p> <\/span><\/span><\/span>Expected Joining Date: <\/b>ASAP
<\/p>Role Summary:<\/b>
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We are looking for an AI\/ML Solution Architect with expertise in Generative AI (GenAI) to help design, build, and deploy cutting\-edge AI solutions. Whether working in the rapid\-paced innovation cycle of a startup or scaling production\-grade GenAI systems for enterprise clients, you will serve as a key enabler of value\-driven, secure, and scalable AI deployments.
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Key Responsibilities:<\/b>
<\/p>\n \n - 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.
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- 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).
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- Design and deliver compelling Solution and SoW and demonstrations of our Generative AI offerings to both technical and non\-technical audiences.
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- Design Retrieval\-Augmented Generation (RAG), prompt engineering strategies, vector database integrations, and model fine\-tuning where required.
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- Translate business objectives into technical roadmaps, collaborating closely with product managers, engineers, and data scientists.
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- Create prototypes and proof\-of\-concepts (PoCs) to validate solution feasibility and performance.
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- Provide technical mentorship, best practices, and governance guidance across teams and clients.
<\/li>\n <\/ul>Skills & Experience Required:<\/b>
<\/p>\n \n - 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)
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- 3\-5 years of experience in AI\/ML development\/solutioning, with at least 1\-2 years in Generative AI\/NLP applications.
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- Strong command of transformers, LLMs, embeddings, and NLP methods.
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- Proficiency with LangChain, LlamaIndex, Hugging Face Transformers, and cloud AI tools (SageMaker, Bedrock, Azure OpenAI, Vertex AI).
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- Experience with vector databases like FAISS, Pinecone, or Weaviate.
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- Familiarity with MLOps practices, including model deployment, monitoring, and retraining pipelines.
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- Skilled in Python, with working knowledge of APIs, Docker, CI\/CD, and RESTful services.
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- Experience in building solutions in both agile startup environments and structured enterprise settings.
<\/li>\n <\/ul>Preferred\/Bonus Skills:<\/b>
<\/p>\n \n - Certifications (e.g., AWS Machine Learning Specialty, Azure AI Engineer).
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- Exposure to multimodal AI (text, image, audio\/video) and Agentic AI.
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- Experience with data privacy, responsible AI, and model interpretability frameworks.
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- Familiarity with enterprise security, scalability, and governance standards.
<\/li>\n <\/ul>Soft Skills:<\/b>
<\/p>\n \n - Entrepreneurial mindset with a bias for action and rapid prototyping.
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- Strong communication and stakeholder management skills.
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- Comfortable navigating ambiguity in startups and structured processes in enterprises.
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- Team player with a passion for continuous learning and AI innovation.
<\/li>\n <\/ul>What We Offer:<\/b>
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