AI Solution Architect

Bengaluru, Karnataka, India

Job Type

Full Time

About the Role

Key Responsibilities

• Architect end-to-end AI/ML deployment solutions focusing on AWS services such as S3, Redshift, SageMaker, Bedrock, Lambda, and IAM, ensuring best practices in security, compliance, and scalability.
• Design and integrate data lakes, structured databases, and ML pipelines leveraging Databricks architecture for smooth data processing and AI workload orchestration.
• Lead solution design and orchestration for RPA and GenAI systems, incorporating conversational and agentic AI platforms like Copilot Studio, Agentforce, and Sierra.
• Drive architectural decisions, review technical approaches, and provide leadership to development teams on experimentation, prototyping, and solution delivery.
• Manage model development, deployment, and lifecycle on platforms such as SageMaker and Bedrock, implementing MLOps best practices.
• Implement end-to-end automation of ML pipelines with SageMaker and Databricks workflows, integrating models into scalable, cloud-native services.
• Utilize Kubernetes and container orchestration for scalable AI deployment alongside infrastructure as code tools such as Terraform and CloudFormation.
• Establish advanced monitoring, logging, and performance optimization for AI workloads, promoting high availability and reliability.
• Collaborate with business stakeholders to prioritize AI use cases and ensure architectural alignment with strategic objectives.
• Oversee data ingestion, transformation, and governance workflows to maintain data privacy, quality, and accessibility for AI and RPA workloads.
• Define and implement CI/CD pipelines tailored for AI/ML deployments, ensuring seamless and automated delivery cycles.
• Stay current on emerging AI technologies, especially in Generative AI and LLM domains, and drive integration of innovative solutions with existing platforms.

Required Skills & Qualifications

• Technical Experience:

o 8-10 years of hands-on solutions architecture experience, with significant focus on AI/ML cloud-native architectures and deployments.

o Deep expertise in core AWS services: S3, Redshift, SageMaker, Bedrock, Lambda, IAM, and associated AI services (Comprehend, Rekognition, Lex, Polly, Textract).

o Proven experience architecting data lakes, ETL pipelines, and managing data engineering workflows (AWS S3, Redshift, Databricks).

o Proficiency in advanced Python programming, Jupyter Notebooks, and machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.

o Experience designing and deploying scalable ML models and pipelines, with strong knowledge of MLOps best practices including automation, containerization, and deployment.

o Expertise with Databricks architecture and integration within ML and AI ecosystems.

o Solid understanding of Kubernetes for container orchestration and infrastructure automation using Terraform or CloudFormation.

o Familiarity with conversational AI, agentic AI platforms, and Generative AI workflows, including LLMs and Bedrock.

o Skilled in API design, system integration, and security best practices governing data privacy and compliance.

o Strong business acumen with the ability to translate technical solutions into business value and prioritize use cases accordingly.

o Experience leading technical teams and cross-functional collaboration to drive AI projects from concept through deployment.

o Excellent communication skills and stakeholder management capabilities in Agile environments.

• Consulting Experience:

o Proven track record in an IT consulting environment, engaging with large enterprises and MNCs in strategic data solutioning projects.

o Strong stakeholder management, business needs assessment, and change management skills.

• Leadership & Soft Skills:

o Experience managing and mentoring small teams, developing technical skills AI & Advanced Analytics domains.

o Ability to influence and align cross-functional teams and stakeholders.

o Excellent communication, documentation, and presentation skills.

o Strong problem-solving, analytical thinking, and strategic vision.

• Educational Qualifications:

o Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.

• Preferred Certifications:

o AWS Certified Solutions Architect – Professional

o AWS Certified Machine Learning – Specialty

o Certified Kubernetes Administrator (CKA) or equivalent

o Terraform Associate or equivalent Infrastructure as Code certifications

o Certified Artificial Intelligence Practitioner (CAIP) or similar AI certifications

o Relevant RPA certifications (UiPath, Blue Prism) a plus

Requirements

Key Responsibilities

• Architect end-to-end AI/ML deployment solutions focusing on AWS services such as S3, Redshift, SageMaker, Bedrock, Lambda, and IAM, ensuring best practices in security, compliance, and scalability.
• Design and integrate data lakes, structured databases, and ML pipelines leveraging Databricks architecture for smooth data processing and AI workload orchestration.
• Lead solution design and orchestration for RPA and GenAI systems, incorporating conversational and agentic AI platforms like Copilot Studio, Agentforce, and Sierra.
• Drive architectural decisions, review technical approaches, and provide leadership to development teams on experimentation, prototyping, and solution delivery.
• Manage model development, deployment, and lifecycle on platforms such as SageMaker and Bedrock, implementing MLOps best practices.
• Implement end-to-end automation of ML pipelines with SageMaker and Databricks workflows, integrating models into scalable, cloud-native services.
• Utilize Kubernetes and container orchestration for scalable AI deployment alongside infrastructure as code tools such as Terraform and CloudFormation.
• Establish advanced monitoring, logging, and performance optimization for AI workloads, promoting high availability and reliability.
• Collaborate with business stakeholders to prioritize AI use cases and ensure architectural alignment with strategic objectives.
• Oversee data ingestion, transformation, and governance workflows to maintain data privacy, quality, and accessibility for AI and RPA workloads.
• Define and implement CI/CD pipelines tailored for AI/ML deployments, ensuring seamless and automated delivery cycles.
• Stay current on emerging AI technologies, especially in Generative AI and LLM domains, and drive integration of innovative solutions with existing platforms.

Required Skills & Qualifications

• Technical Experience:

• 8-10 years of hands-on solutions architecture experience, with significant focus on AI/ML cloud-native architectures and deployments.

• Deep expertise in core AWS services: S3, Redshift, SageMaker, Bedrock, Lambda, IAM, and associated AI services (Comprehend, Rekognition, Lex, Polly, Textract).
• Proven experience architecting data lakes, ETL pipelines, and managing data engineering workflows (AWS S3, Redshift, Databricks).
• Proficiency in advanced Python programming, Jupyter Notebooks, and machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.
• Experience designing and deploying scalable ML models and pipelines, with strong knowledge of MLOps best practices including automation, containerization, and deployment.
• Expertise with Databricks architecture and integration within ML and AI ecosystems.
• Solid understanding of Kubernetes for container orchestration and infrastructure automation using Terraform or CloudFormation.
• Familiarity with conversational AI, agentic AI platforms, and Generative AI workflows, including LLMs and Bedrock.
• Skilled in API design, system integration, and security best practices governing data privacy and compliance.
• Strong business acumen with the ability to translate technical solutions into business value and prioritize use cases accordingly.
• Experience leading technical teams and cross-functional collaboration to drive AI projects from concept through deployment.

• Excellent communication skills and stakeholder management capabilities in Agile environments.

• Consulting Experience:

• Proven track record in an IT consulting environment, engaging with large enterprises and MNCs in strategic data solutioning projects.

• Strong stakeholder management, business needs assessment, and change management skills.

• Leadership & Soft Skills:

• Experience managing and mentoring small teams, developing technical skills AI & Advanced Analytics domains.

• Ability to influence and align cross-functional teams and stakeholders.
• Excellent communication, documentation, and presentation skills.

• Strong problem-solving, analytical thinking, and strategic vision.

• Educational Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.

• Preferred Certifications:

• AWS Certified Solutions Architect – Professional

• AWS Certified Machine Learning – Specialty
• Certified Kubernetes Administrator (CKA) or equivalent
• Terraform Associate or equivalent Infrastructure as Code certifications
• Certified Artificial Intelligence Practitioner (CAIP) or similar AI certifications
• Relevant RPA certifications (UiPath, Blue Prism) a plus

About the Company

Cigres Technologies Private Limited is a technology consulting and services company that focuses on helping clients resolve their significant digital problems and enabling radical digital transformation using multiple technologies on premise or in the cloud. The company was founded with the goal of leveraging cutting-edge technology to deliver innovative solutions to clients across various industries.