Gen AI Architect

Position/TITLE: Gen AI Architect

Location :  Onsite – USA

Overview:  As a Solution Architect, you will play a pivotal role in designing, developing, and implementing artificial intelligence solutions tailored to meet the business needs of our organization and clients. You will collaborate with cross-functional teams to understand requirements, assess feasibility, and architect AI systems that leverage cutting-edge technologies. Your expertise will drive innovation, efficiency, and scalability in AI-driven initiatives, ensuring alignment with business objectives and industry best practices.

Responsibilities:

Solution Design:  Design end-to-end AI solutions encompassing data ingestion, preprocessing, model development, deployment, and monitoring, ensuring scalability, reliability, and performance.

Requirement Analysis:  Collaborate with stakeholders to gather and analyze requirements, identifying opportunities for AI integration to address business challenges and achieve strategic goals.

Technology Evaluation:  Research and evaluate emerging AI technologies, frameworks, and tools to recommend optimal solutions that align with project requirements, budget constraints, and future scalability.

Architecture Development:  Define system architectures, data flow diagrams, and technical specifications for AI solutions, considering factors such as security, compliance, and interoperability with existing systems.

Integration & Deployment:  Oversee the integration of AI solutions with existing infrastructure, applications, and workflows, collaborating with DevOps and IT teams to ensure seamless deployment and maintenance.

Performance Optimization:  Identify bottlenecks and optimize AI algorithms, workflows, and infrastructure to enhance system performance, scalability, and cost-effectiveness.

Quality Assurance:  Establish testing strategies and quality assurance processes to validate the accuracy, reliability, and robustness of AI solutions, conducting thorough testing and debugging as needed.

Documentation & Training:  Create comprehensive documentation, user guides, and training materials for AI solutions, facilitating knowledge transfer and ensuring effective adoption by end-users and stakeholders.

Continuous Improvement:  Stay abreast of industry trends, best practices, and advancements in Cloud and AI technologies, advocating for innovation and driving continuous improvement in solution architecture and development processes.

Responsibilities:  

Technical Skills – Must have  

1. Proven experience (10 years) in designing and implementing AI solutions, with expertise in machine learning, deep learning, natural language processing and more than 5 years of experience as a Solution Architect.

2. Hands-on experience with cloud platforms (AWS Cloud) and AI services (e.g. SageMaker) for building and deploying AI solutions at scale.

3. In-depth knowledge of software architecture principles, microservices architecture, containerization (e.g., Docker, Kubernetes), and distributed computing.

4. Hands-on Experience with Bedrock, Amazon Q, Open AI, Gemini, Copilot, LLMs – Claude, Cohere, GPT, etc

5. A passion for Generative AI, and an understanding of strengths and weaknesses of Generative LLM's

6. OWASP and Application security

7. Strong proficiency in programming languages such as Python, R, Java, C# or Scala, with experience in frameworks like TensorFlow, PyTorch, scikit-learn, or Keras.

8. Excellent problem-solving skills, analytical thinking, and attention to detail, with the ability to translate complex requirements into practical AI solutions.

9. Strong communication and collaboration skills, with the ability to effectively interact with stakeholders across different levels of the organization.

10. Relevant certifications (e.g., AWS Certified Solutions Architect,  AWS Certified Machine Learning - Specialty) is a plus.

Technical Skills – Good to have:

1. Experience in MLOps tools and frameworks (e.g., MLflow, Kubeflow, TensorFlow Extended).

2. Expertise in conversational system architecture

3. Knowledge of big data technologies

4. Knowledge on Statistical Methods

5. Knowledge on Linux / Unix Flavors

Education Qualifications:  

· Bachelor's degree in Computer Science, Information Technology, or related field (Master's degree preferred).  

Process Skills:  

· General SDLC processes  

· Understanding of utilizing Agile and Scrum software development methodologies  

· Skill in gathering and documenting user requirements and writing technical specifications.   

Behavioral Skills:   

· Work closely with designers, Architects, data scientists, product managers, and other engineers to deliver comprehensive solutions.  

· Communicate effectively and share technical knowledge with the team.  

· Be open to feedback and continuously learn and adapt to new technologies.  

· Ability to work independently and as part of a team.  

· Passion for learning and staying updated on the latest technologies.  

· Good Attitude and Quick learner.  

Certification  (Good to have) :  

· AWS Certified Solutions Architect   

· AWS Certified Machine Learning - Specialty

· AI/ML certification