Principal Architect

We are currently hiring for immediate joiners for the below JD

please apply only if you can able to join immediately

Role Overview
We are seeking a highly experienced Principal Architect to lead the design and delivery of advanced AI/ML and Generative AI solutions. This role requires deep expertise in machine learning, deep learning, NLP, and emerging agentic frameworks, along with strong architectural vision to solve complex business challenges.
The ideal candidate will combine technical depth, strategic thinking, and executive-level communication to translate business needs into scalable, production-grade AI systems.
Key Responsibilities
1. Architecture & Solution Design
Define end-to-end architecture for AI/ML, NLP, and GenAI solutions.
Design scalable RAG (Retrieval Augmented Generation) architectures for enterprise use cases.
Lead architecture for agentic systems and autonomous workflows using modern frameworks.
Ensure systems are scalable, secure, fault-tolerant, and production-ready.
2. Technical Leadership
Provide hands-on leadership in Python-based AI/ML development.
Guide teams on selecting and implementing appropriate ML and deep learning models.
Mentor engineering teams and establish best practices, coding standards, and governance.
Drive adoption of MLOps and LLMOps practices.
3. AI/ML & GenAI Expertise
Apply advanced knowledge of:
Machine Learning Algorithms (supervised, unsupervised, reinforcement learning)
Deep Learning frameworks and architectures
Natural Language Processing (NLP) and Large Language Models (LLMs)
Design and optimize RAG pipelines for performance and accuracy.
Evaluate and implement agentic frameworks (AutoGPT, LangChain agents, etc.) for enterprise automation.
4. Business Alignment & Strategy
Engage with stakeholders to articulate business problems and define strategic solutions.
Translate business requirements into technical architecture and roadmaps.
Drive innovation by identifying AI opportunities that deliver measurable business value.
Present architectural decisions and solution approaches to senior leadership.
5. Governance & Best Practices
Establish guidelines for model development, deployment, monitoring, and ethical AI usage.
Ensure compliance with data privacy, security, and regulatory standards.
Drive reusable frameworks, accelerators, and reference architectures.
Required Skills & Qualifications
Technical Skills
Strong proficiency in Python (mandatory)
Solid understanding of:
Machine Learning Algorithms
Deep Learning Concepts
Natural Language Processing (NLP)
Hands-on experience with:
RAG Architectures
Agentic Frameworks (LangChain, AutoGen, CrewAI, etc.)
Familiarity with LLM ecosystems (OpenAI, Azure OpenAI, Hugging Face, etc.)
Exposure to statistics (preferred but not mandatory)
Architecture & Platforms
Experience in designing AI platforms and enterprise-scale solutions
Knowledge of cloud platforms (Azure/AWS/GCP)
Understanding of data engineering pipelines and distributed systems
Soft Skills
Strong ability to articulate complex business challenges and propose strategic solutions
Excellent communication and stakeholder management skills
Proven ability to influence executive decision-making
Experience Requirements
12+ years of overall experience with significant exposure to AI/ML architecture
Proven track record in delivering enterprise AI or GenAI solutions
Experience leading cross-functional teams and large-scale programs