Job Description For Senior Principal AI Architect
Detail Information
Job Title: Senior Principal AI Architect
Company: NCG
Location: Pune
Experience Required: Level 6 (12-15 Yrs) - Initiate, Influence
Open Positions: 1
Posting Date: 2026-04-22T11:32:30+05:30
Employment Type: Full-time
Overview:
As a Senior Principal AI Architect, you will spearhead the innovation and strategic deployment of AI ecosystems within the Life Sciences sector. This role is pivotal in bridging advanced AI research with practical, scalable business solutions. With a focus on both Classical Machine Learning and Generative AI, you will lead the architectural design of autonomous systems and robust cloud-native AI systems. The position requires a deep understanding of AI/ML systems and the ability to tackle complex data architecture challenges, ensuring secure, scalable, and efficient data platforms. You will work across multi-cloud environments, including AWS, Azure, and GCP, to deploy resilient AI infrastructures. In this influential role, you will define and implement cutting-edge AI strategies, ensuring all systems are compliant with global standards and ethical AI practices. Your leadership will drive the development of innovative AI solutions that align with our organization's mission and goals, enhancing our capabilities in the Life Sciences domain. Working closely with cross-functional teams, you will guide the design of advanced AI frameworks, leveraging the latest technologies to optimize workflows and achieve high-impact results. This position demands a visionary leader capable of translating complex AI concepts into actionable strategies that deliver measurable business outcomes.
We are looking for Senior Principal AI Architect in the Life Sciences sector:
- Architect scalable, low-latency AI/ML systems integrating Classical ML and Generative AI for enterprise solutions.
- Design autonomous AI agents and complex reasoning workflows using modern frameworks such as LangGraph and AutoGen.
- Engineer conversational memory architectures and state management protocols for long-term agentic tasks.
- Develop advanced Retrieval-Augmented Generation (RAG) pipelines with vector databases to enhance AI accuracy and mitigate hallucinations.
- Lead multi-cloud AI infrastructure deployment and strategy across AWS, Azure, and GCP, ensuring high availability and resilience.
- Solve data engineering challenges, architecting solutions integrated with platforms like Snowflake and Databricks.
- Translate proofs of concept into production systems, establishing patterns for model serving and load balancing.
- Oversee MLOps and LLMOps practices, including CI/CD, model evaluation, and system observability.
You Might Be Our Ideal Match If You:
- 12+ years of experience in software engineering and architecture, with 5+ years in AI/ML architecture.
- Expertise in Generative AI and foundational models such as GPT, Llama, and Gemini, with experience in fine-tuning and prompt engineering.
- Proficiency in agentic and orchestration frameworks like LangChain and LangGraph.
- Extensive experience with cloud platforms (AWS, Azure, GCP) and container orchestration with Docker and Kubernetes.
- Proficiency in modern data stack technologies, including vector and graph databases, and data warehousing.
- Expert-level proficiency in Python; strong skills in Go, Java, or C++ are highly preferred.
- Proven leadership skills with the ability to communicate complex AI concepts to C-level executives and engineering teams.
Education:
Bachelor's in Computer Science, Engineering, or related technical field.
Overview
As a Senior Principal AI Architect, you will spearhead the innovation and strategic deployment of AI ecosystems within the Life Sciences sector. This role is pivotal in bridging advanced AI research with practical, scalable business solutions. With a focus on both Classical Machine Learning and Generative AI, you will lead the architectural design of autonomous systems and robust cloud-native AI systems. The position requires a deep understanding of AI/ML systems and the ability to tackle complex data architecture challenges, ensuring secure, scalable, and efficient data platforms. You will work across multi-cloud environments, including AWS, Azure, and GCP, to deploy resilient AI infrastructures. In this influential role, you will define and implement cutting-edge AI strategies, ensuring all systems are compliant with global standards and ethical AI practices. Your leadership will drive the development of innovative AI solutions that align with our organization's mission and goals, enhancing our capabilities in the Life Sciences domain. Working closely with cross-functional teams, you will guide the design of advanced AI frameworks, leveraging the latest technologies to optimize workflows and achieve high-impact results. This position demands a visionary leader capable of translating complex AI concepts into actionable strategies that deliver measurable business outcomes.
Key Responsibilities
- Architect scalable, low-latency AI/ML systems integrating Classical ML and Generative AI for enterprise solutions.
- Design autonomous AI agents and complex reasoning workflows using modern frameworks such as LangGraph and AutoGen.
- Engineer conversational memory architectures and state management protocols for long-term agentic tasks.
- Develop advanced Retrieval-Augmented Generation (RAG) pipelines with vector databases to enhance AI accuracy and mitigate hallucinations.
- Lead multi-cloud AI infrastructure deployment and strategy across AWS, Azure, and GCP, ensuring high availability and resilience.
- Solve data engineering challenges, architecting solutions integrated with platforms like Snowflake and Databricks.
- Translate proofs of concept into production systems, establishing patterns for model serving and load balancing.
- Oversee MLOps and LLMOps practices, including CI/CD, model evaluation, and system observability.
Requirements
- 12+ years of experience in software engineering and architecture, with 5+ years in AI/ML architecture.
- Expertise in Generative AI and foundational models such as GPT, Llama, and Gemini, with experience in fine-tuning and prompt engineering.
- Proficiency in agentic and orchestration frameworks like LangChain and LangGraph.
- Extensive experience with cloud platforms (AWS, Azure, GCP) and container orchestration with Docker and Kubernetes.
- Proficiency in modern data stack technologies, including vector and graph databases, and data warehousing.
- Expert-level proficiency in Python; strong skills in Go, Java, or C++ are highly preferred.
- Proven leadership skills with the ability to communicate complex AI concepts to C-level executives and engineering teams.
Education
Bachelor's in Computer Science, Engineering, or related technical field.
