Solution Architect

Position : Solutions Architect - AI

Experience : 14-20 Years

Role Overview

We are seeking a highly experienced AI Solutions Architect with a strong background in software development and a proven track record of leading AI/ML initiatives at scale. The ideal candidate will combine hands-on technical expertise with strategic leadership to architect innovative AI-driven solutions that align with organizational objectives.

This role demands deep knowledge in Generative AI, large-scale AI deployments, vector databases, prompt engineering, and cloud AI/ML ecosystems, along with the ability to translate complex business problems into scalable technical architectures.

Key Responsibilities :

AI/ML Solution Architecture :

- Lead the design and implementation of AI/ML solutions across multiple business units, ensuring alignment with strategic objectives.

- Architect scalable, secure, and high-performance AI platforms, integrating Generative AI, LLMs, and advanced AI paradigms (RAG, Agentic AI, base model fine-tuning).

- Define solution architecture for prompt engineering, embedding pipelines, and vector database integration.

- Establish best practices for AI model deployment, lifecycle management, and monitoring at scale.

Cloud & Infrastructure :

- Leverage cloud-native AI/ML services on AWS, Azure, or GCP to implement robust AI solutions.

- Design cloud architectures for large-scale data processing, AI inference pipelines, and real-time arbitration use cases.

- Ensure integration with existing enterprise systems, databases (SQL/NoSQL), and vector storage systems.

Technical Leadership & Governance :

- Serve as the technical lead for AI/ML projects, mentoring teams of data scientists, ML engineers, and software developers.

- Define data compliance, security protocols, and AI governance frameworks, ensuring ethical and fair AI implementations.

- Collaborate with legal, business, and risk management teams to ensure AI deployments meet regulatory and ethical standards.

Business & Stakeholder Engagement :

- Act as the bridge between technical teams and business stakeholders, translating technical capabilities into actionable business solutions.

- Analyze complex business requirements and architect AI-driven digital transformation initiatives to optimize workflows and decision-making.

- Oversee the delivery of AI-enabled platforms, ensuring on-time execution, adherence to quality standards, and measurable business impact.

Innovation & Continuous Improvement :

- Research, evaluate, and implement emerging AI frameworks, generative models, and vector database technologies.

- Drive adoption of advanced prompt design patterns, embedding techniques, and model fine-tuning strategies.

- Foster a culture of innovation and AI-driven experimentation across the organization.

Required Skills & Expertise :

Technical Skills :

- 14-20 years of software development experience with at least 5+ years in AI/ML and 3+ years in an architectural/leadership role.

- Hands-on experience with Generative AI frameworks, LLMs, RAG, Agentic AI, and base model fine-tuning.

- Strong prompt engineering and design patterns expertise.

- Deep knowledge of vector databases, embeddings, semantic search, and AI-driven retrieval systems.

- Proficiency in cloud AI/ML services (AWS SageMaker, Azure ML, GCP Vertex AI, etc.) and deployment pipelines.

- Strong understanding of databases (SQL, NoSQL), distributed data systems, and ETL/data pipelines.

- Expertise in security, data compliance, and AI governance frameworks.

- Knowledge of AI ethics, fairness, explainability, and responsible AI practices.

Leadership & Business Skills :

- Excellent communication, stakeholder management, and change management skills.

- Experience in large-scale digital platform design with AI integration.

- Ability to translate complex AI/ML technical concepts into business value propositions.

- Proven track record of mentoring technical teams and driving AI strategy across an organization.

Preferred Qualifications :

- Advanced degree in Computer Science, AI/ML, Data Science, or related fields.

- Previous experience delivering real-time AI platforms for high-stakes applications (finance, arbitration, healthcare, or enterprise SaaS).

- Hands-on familiarity with MLOps frameworks, CI/CD pipelines for AI/ML, model versioning, and monitoring.