Artificial Intelligence Solutions Architect | Okhla | 5-9 yrs

The Artificial Intelligence Solutions Architect will be responsible for designing, architecting, and guiding the implementation of enterprise-grade AI solutions with a strong focus on Retrieval-Augmented Generation (RAG) and hybrid RAG architectures. This role bridges business requirements and advanced AI engineering, ensuring scalable, secure, and production-ready AI systems. The position requires hands-on architectural depth combined with the ability to influence technical direction and mentor engineering teams.

• Architect end-to-end AI solutions with a focus on RAG and hybrid RAG implementations for enterprise use cases.
• Design scalable, secure, and cost-efficient AI system architectures aligned with business objectives.
• Define and govern AI solution blueprints, reference architectures, and best practices.
• Lead the integration of NLP, reinforcement learning, and machine learning pipelines into production systems.
• Establish MLOps frameworks for model lifecycle management, monitoring, versioning, and deployment.
• Collaborate with product, engineering, data, and DevOps teams to translate requirements into robust technical designs.
• Ensure AI solutions adhere to data privacy, security, and enterprise governance standards.
• Review solution quality through architectural reviews, technical validations, and implementation checkpoints.

• Proven hands-on experience as an AI / ML Solutions Architect or similar role in enterprise environments.
• Strong expertise in RAG and hybrid RAG architectures, including retrieval strategies and vector-based systems.
• Deep understanding of NLP techniques and large language model integration patterns.
• Experience designing and operating MLOps pipelines for training, deployment, monitoring, and retraining.
• Working knowledge of reinforcement learning concepts and applied use cases.
• Ability to design cloud-native, scalable, and resilient AI architectures for production workloads.
• Strong documentation, architectural communication, and stakeholder engagement skills.
  

• Experience with multi-tenant or SaaS-based AI platforms.
• Exposure to AI cost optimization, observability, and performance tuning.
• Familiarity with responsible AI, governance, and explainability frameworks.
• Experience working with globally distributed engineering teams.
  

• Experience with modern LLM ecosystems and AI orchestration frameworks.
• Exposure to vector databases, embedding models, and retrieval pipelines.
• Working knowledge of cloud platforms and containerized deployments.
• Familiarity with CI/CD and infrastructure-as-code practices for ML systems.
  

• Architecting and evolving enterprise-grade AI and agentic AI platforms.
• Designing and improving hybrid RAG pipelines for high-accuracy, low-latency applications.
• Defining MLOps standards and deployment patterns for scalable AI systems.
• Supporting multiple business domains with reusable AI architecture frameworks.
• Enabling engineering teams with clear architectural direction and best practices.
  

Mobiloitte is a global technology consulting and engineering organization delivering enterprise-scale solutions across AI, data, cloud, mobility, and emerging technologies. With a strong focus on building production-ready, secure, and scalable systems, Mobiloitte partners with enterprises, governments, and fast-growing organizations worldwide to solve complex business and technology challenges. The company emphasizes engineering discipline, innovation with purpose, and long-term client and employee success.

• Work closely with product managers, data scientists, architects, and engineering leaders.
• Operate within a structured, process-driven engineering environment.
• Encourage ownership, accountability, and high-quality technical outcomes.
• Support continuous learning and architectural excellence across teams.
  

• Competitive compensation; salary is not a constraint for the right candidate .
• Long-term career growth in advanced AI and enterprise platforms.
• Exposure to complex, real-world AI systems at scale.
• Flexible work arrangements within a professional, outcome-driven environment.

Thanks

Team- HR