Website:
planetlink.in
Job details:
Job Description – Solution Architect – AI
Experience - 15–20 Years
Role Overview
We are looking for a highly experienced AI Solution Architect with 15–20 years of overall technology experience and strong expertise in designing, architecting, and delivering enterprise-scale AI/ML solutions.
The ideal candidate will have a strong combination of AI/ML, Generative AI, Cloud, Data Engineering, Software Architecture, MLOps and Enterprise Architecture experience. The candidate will work closely with business stakeholders, technology teams and senior leadership to translate business requirements into scalable, secure and commercially viable AI solutions.
Key Responsibilities
- Define end-to-end architecture for enterprise AI, ML and Generative AI solutions.
- Translate business and functional requirements into scalable technical architectures.
- Design AI/ML platforms, data pipelines, APIs, microservices and integration architectures.
- Architect and implement Generative AI, LLM, RAG and Agentic AI solutions.
- Evaluate and select appropriate AI models, frameworks, cloud platforms and technology stacks.
- Design solutions using AWS, Azure and/or Google Cloud AI/ML services.
- Establish architecture standards for model development, deployment, monitoring and governance.
- Lead implementation of MLOps and LLMOps frameworks.
- Design secure and scalable AI solutions considering performance, availability, cost and compliance.
- Work with data engineering teams on data lakes, data warehouses, feature stores and data pipelines.
- Define approaches for model training, fine-tuning, evaluation, deployment and monitoring.
- Design RAG architectures using vector databases and enterprise knowledge sources.
- Guide engineering teams on APIs, microservices, containers and cloud-native architectures.
- Conduct technology evaluations, PoCs and architecture assessments.
- Provide technical leadership to AI/ML engineers, data scientists, developers and DevOps teams.
- Identify opportunities to improve business processes through AI automation.
- Ensure responsible AI practices, including security, privacy, explainability, governance and model risk management.
- Create architecture diagrams, technical specifications, solution blueprints and implementation roadmaps.
- Present proposed solutions and architectural decisions to CXO-level stakeholders and clients.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, AI or a related discipline.
- 15–20 years of overall IT experience.
- Significant experience in Solution Architecture / Enterprise Architecture.
- Minimum 5+ years of experience in AI/ML and/or Data Engineering, with strong recent exposure to Generative AI.
- Proven experience architecting and delivering large-scale enterprise solutions.
- Strong client-facing and stakeholder-management capabilities.
Soft Skills
- Excellent communication and presentation skills.
- Strong analytical and problem-solving ability.
- Ability to communicate complex AI concepts to both technical and non-technical stakeholders.
- Strong leadership and mentoring capabilities.
- Strategic thinking combined with hands-on technical understanding.
- Strong consulting and client-management skills.
- Ability to work across business, product, data and technology teams.
Key Deliverables
- Enterprise AI Solution Architecture.
- GenAI/LLM/RAG architecture and technical blueprints.
- AI platform and integration architecture.
- Technology evaluation and PoC recommendations.
- Cloud and infrastructure architecture.
- AI implementation roadmap.
- Security and governance architecture.
- Technical documentation and architecture decision records.
- Guidance and technical leadership for development and implementation teams.
Ideal Candidate Profile
The ideal candidate is a hands-on, enterprise-level AI Solution Architect who can move beyond individual AI models and design complete business solutions—from data ingestion and model selection through LLM/RAG/Agentic AI, APIs, cloud infrastructure, security, deployment, monitoring and production operations.
Experience working with large enterprises, global clients and complex transformation programs will be highly preferred.
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