Artificial Intelligence Architect
- Qentelli
- 10 - 20 years
- Hyderabad
- 1 month ago
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Job Description
Job Summary
We are looking for a highly experienced Technical Architect with strong expertise in solution architecture and AI/ML technologies. This role is responsible for evaluating AI feasibility, designing scalable AI/ML solutions, and owning end-to-end implementation across platforms.
The ideal candidate will define architecture standards, guide engineering teams, and ensure seamless system integration while maintaining governance and best practices. You will play a critical role in transforming business requirements into robust, scalable, and production-ready AI solutions.
Roles and Responsibilities
Solution Architecture & Design
- Define end-to-end solution architecture for AI/ML-driven systems aligned with business objectives.
- Design scalable, secure, and high-performance architectures across cloud, on-prem, or hybrid environments.
- Create architecture blueprints, technical design documents, and solution diagrams.
AI Feasibility Analysis
- Evaluate business problems and assess feasibility of AI/ML approaches.
- Identify suitable AI/ML techniques (e.g., NLP, computer vision, predictive analytics).
- Conduct cost-benefit and risk analysis for AI initiatives.
- Recommend build vs buy vs partner decisions.
AI/ML Solution Design
- Design AI/ML pipelines including data ingestion, preprocessing, model training, validation, deployment, and monitoring.
- Collaborate with data scientists to select models, frameworks, and tools.
- Ensure scalability, reliability, and maintainability of AI systems.
- Address ethical AI considerations, bias mitigation, and explainability.
End-to-End Implementation Ownership
- Own the technical delivery of AI/ML solutions from concept to production.
- Oversee development, integration, testing, and deployment phases.
- Ensure adherence to timelines, quality standards, and architectural guidelines.
- Troubleshoot complex technical challenges across the lifecycle.
System Integration Strategy
- Define integration patterns between AI components and enterprise systems (ERP, CRM, data platforms, APIs).
- Ensure interoperability across microservices, legacy systems, and third-party platforms.
- Design API strategies, event-driven architectures, and data exchange mechanisms.
Architecture Governance
- Establish and enforce architecture standards, guidelines, and best practices.
- Conduct architecture reviews and ensure compliance with enterprise standards.
- Manage technical risks and ensure security, scalability, and performance.
- Drive reusability and standardization across solutions.
Stakeholder Collaboration
- Work closely with product managers, engineering teams, data scientists, and business stakeholders.
- Translate business requirements into technical solutions.
- Provide technical leadership and mentorship to development teams.
Innovation & Continuous Improvement
- Stay updated with emerging AI/ML technologies and architecture trends.
- Identify opportunities to enhance systems with advanced AI capabilities.
- Promote innovation and adoption of modern architectural patterns.
Required Skills
Solution Architecture
- Strong experience in designing enterprise-level solutions and distributed systems.
- Expertise in architecture patterns (microservices, event-driven, serverless).
- Ability to create detailed architecture documentation and diagrams.
AI/ML Expertise
- Solid understanding of machine learning, deep learning, and AI concepts.
- Experience designing and implementing AI/ML solutions in production.
- Familiarity with frameworks like TensorFlow, PyTorch, or similar.
AI Feasibility & Strategy
- Ability to evaluate use cases and determine AI applicability.
- Strong analytical skills for assessing ROI, risks, and technical feasibility.
System Integration
- Experience integrating AI solutions with enterprise systems and APIs.
- Knowledge of middleware, messaging systems (Kafka, RabbitMQ), and ETL pipelines.
Cloud & Infrastructure
- Hands-on experience with cloud platforms (AWS, Azure, GCP).
- Knowledge of containerization (Docker) and orchestration (Kubernetes).
- Understanding of CI/CD pipelines and DevOps practices.
Governance & Best Practices
- Experience in defining architecture governance frameworks.
- Strong understanding of security, compliance, and data privacy standards.
Communication & Leadership
- Excellent stakeholder communication and presentation skills.
- Proven ability to lead technical teams and influence decisions.
- Strong mentoring and coaching abilities.
Preferred Skills
- Experience with Generative AI, LLMs, and AI copilots.
- Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker).
- Experience with big data technologies (Spark, Hadoop).
- Knowledge of data governance, data quality, and lineage tools.
- Exposure to domain-specific AI applications (finance, healthcare, retail).
- Experience with real-time AI systems and streaming architectures.
- Understanding of Responsible AI frameworks and model explainability tools.
Nice-to-Have Qualifications
- Bachelors or Masters degree in Computer Science, Engineering, or related field.
- 815+ years of experience in software engineering/architecture roles.
- Certifications in cloud platforms (AWS Certified Solutions Architect, Azure Architect, etc.).
- Prior experience in leading large-scale digital transformation or AI initiatives.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Solution ArchitectEmployement Type: Full timeContact Details:
Company: QentelliLocation(s): Hyderabad
Keyskills: Artificial Intelligence Machine Learning Technical Architecture Ai Solutions Aiml AI Implementation Architecture Analysis AIML Solution Governance
Qentelli
Qentelli at Glance:- Qentelli is a technology company that accelerates digital transformation and cloud transformation journeys through DevOps, Automation, Agile transformation, AI and Deep learning. Forrester recently recognized our efforts at using AI and ML in the augme...
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