Hiring: AI Solution Architect
Client Name: Corover.ai
Immediate Joiners Preferred
Educational Qualification
- B.Tech./M.Tech./M.S./Ph.D. in Computer Science, IT, AI, or a related technical field.
Mandatory Experience
- Minimum 8–12 years of overall professional experience.
- At least 4–5 years in enterprise AI/ML solution architecture or large-scale data systems.
- Experience designing and deploying multi-component AI solutions in enterprise or government environments.
Mandatory Technical Skills
- Architecture: Microservices, serverless architecture, event-driven and domain-driven design, data architecture, and model lifecycle architecture.
- Cloud: AWS Bedrock, SageMaker, Lambda, API Gateway, S3; Azure OpenAI Service, Azure ML Studio, AKS; GCP Vertex AI, BigQuery, Cloud Storage.
- AI frameworks: TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LLM orchestration, prompt engineering, and Responsible AI.
- Data and storage: SQL, PostgreSQL, MySQL, MongoDB, DynamoDB, Pinecone, and Weaviate.
- Integration: REST APIs, GraphQL, WebSocket, enterprise integration, and interoperability frameworks.
- Conversational AI: Speech-to-Text, Text-to-Speech, chatbot pipelines, RAG, vector stores, and LLM integration.
- Security: IAM, RBAC, encryption at rest and in transit, data privacy, and AI governance.
Key Responsibilities
- Design end-to-end AI/ML solution architectures and integrations with enterprise and government platforms.
- Define APIs, interoperability standards, data flows, security, scalability, and deployment architecture.
- Evaluate cloud-native and on-premises deployment models.
- Lead architecture reviews, technical governance, and mentoring of engineering teams.
Preferred: AWS/Azure/GCP architecture certifications, research papers, case studies, and open-source contributions.
Pay: ₹2,200,000.00 - ₹4,200,000.00 per year
Application Question(s):
- What is your highest educational qualification?
- How many years of total professional experience do you have?
- How many years of experience do you have in enterprise AI/ML solution architecture or large-scale data systems?
- Have you designed and deployed multi-component AI solutions in enterprise or government environments?
- Which cloud AI platforms have you worked with hands-on?
- Do you have experience designing microservices, serverless, event-driven, and domain-driven architectures?
- Have you implemented LLM-based solutions using RAG, vector databases, and LLM orchestration frameworks such as LangChain?
- Which AI/ML frameworks have you used professionally?
- Do you have experience designing secure AI systems with IAM/RBAC, encryption, data privacy, and AI governance?
- Have you led architecture reviews, defined enterprise integrations/APIs, and mentored engineering teams?
- Do you hold AWS, Azure, or GCP architecture certifications, or have relevant research papers/open-source contributions?
- How soon you can join
Work Location: In person
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