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.(ref : hirist.tech)