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Job Position - Solution Architect (AI & Product Engineering)
Experience Required - 7-10 years
Job Type - Full time
Location - Hyderabad, India
Overview
We are seeking a visionary leader with extensive experience in AI-based product innovation and development to drive the integration of advanced AI, Generative AI, and Multimodal AI systems into innovative solutions. This role requires a deep understanding of AI ecosystems to build strategic partnerships and onboard top talent while also possessing expertise in patent filing to protect intellectual property.
Role and Responsibilities
AI AI/ML Solution Architecture & Design
- Design comprehensive AI solution architectures that are scalable, maintainable, and
aligned with business objectives
- Create detailed architectural diagrams, technical specifications, and solution blueprints
- Evaluate and recommend AI frameworks, models, and tools (e.g., TensorFlow, PyTorch,
LangChain (AutoML).
- Define data strategies for AI model training, including data pipelines, storage,
feature engineering
- Optimize data processing workflows for real-time and batch AI applications.
Cloud & Infrastructure
- Architect and deploy AI solutions on GCP, AWS, Azure, or OCI, optimizing for cost,
performance, and scalability.
- Implement containerized AI workloads (Docker, Kubernetes) and serverless AI solutions.
- Design high-availability, fault-tolerant, and secure AI infrastructure.
Data Architecture & Management
- Design and implement data architectures that support effective AI model deployment
- Define data pipelines, storage strategies, and data governance frameworks
- Establish data lineage and metadata management practices while integrating big data
technologies (Spark, Databricks, Snowflake) for AI-driven analytics.
MLOps & DevOps
- Build end-to-end MLOps pipelines (MLflow, Kubeflow, SageMaker, Vertex AI) for model
lifecycle management.
- Implement CI/CD for AI models, including automated testing, versioning, and rollback.
- Design monitoring, logging, and alerting for AI models in production.
Technical Leadership
- Lead the development of end-to-end AI solutions from conception to deployment
- Collaborate with cross-functional teams, including data scientists, engineers, and product
managers
- Provide technical guidance and mentorship to development teams
- Conduct architectural reviews and ensure adherence to design principles
Performance & Optimization
- Monitor and optimize AI system performance, latency, and resource utilization
- Implement cost optimization strategies for AI infrastructure and operations
- Conduct capacity planning and scaling strategies for AI workloads
- Troubleshoot and resolve complex AI system issues
Innovation & Research
- Stay current with emerging AI technologies, frameworks, and industry trends
- Evaluate and pilot new AI tools and technologies for potential adoption
- Drive innovation initiatives and proof-of-concept development
- Participate in AI community events and knowledge sharing
Stakeholder Engagement
- Present technical solutions and architectural designs to stakeholders and leadership
- Collaborate effectively with business teams, sales, and business development teams to
support pre-sales activities, including presentations and demonstrations, to understand
requirements and constraints.
- Facilitate technical discussions and decision-making processes
Experience Requirement
- 7+ years of total professional experience in technology and solution architecture
- 2+ years of hands-on experience in AI/ML solution development and implementation
- 5+ years of experience working with cloud platforms (GCP, AWS, Azure, OCI)
Technical Skills
- AI/ML Frameworks: TensorFlow, PyTorch, Hugging Face, LangChain, AutoML.
- Cloud AI Services: SageMaker, Vertex AI, Azure ML, Bedrock, LLM APIs.
- MLOps Tools: MLflow, Kubeflow, TFX, Docker, Kubernetes, CI/CD pipelines.
- Data Engineering: Spark, Databricks, BigQuery, Snowflake, Airflow.
- Programming: Python (advanced), Java/Scala, SQL, PySpark.
- Agentic AI: RPA tools (UiPath, Automation Anywhere), process mining.
- Hands-on experience with CI/CD pipelines and DevOps practices
Preferred Qualifications
- Master's degree in Computer Science, Engineering, or related technical field
- Certifications in cloud platforms (GCP Professional Cloud Architect, AWS Solutions
Architect, Azure Solutions Architect)
- Experience with real-time AI applications and streaming data processing
- Knowledge of AI ethics, bias detection, and responsible AI practices
- Experience with microservices architecture and API design
- Strong programming skills in Python, TensorFlow, PyTorch, scikit-learn, and other
relevant AI development tools and frameworks.
Soft skill
- Excellent communication and presentation skills
- Strong collaborative mindset with ability to work across diverse teams
- Leadership capabilities with experience mentoring technical team members
- Problem-solving skills with the ability to think strategically and analytically
- Adaptability to work in a fast-paced, evolving technology environment