Solution/Tech Architect - AI
ApTask
- Dallas, TX
- $130,000-150,000 per year
- Permanent
- Full-time
Type of hire: FTE only.
Salary range: 130-150 K + Benefits.
Yrs. of exp:- between 12-18 yrs.Location: Mostly Remote.
Note: Pls share profiles based out of NY/NJ/ Dallas, TX/Huston, TX.
JD:
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.
- Proven experience (3 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.
- Hands-on experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and AI services (e.g., VertexAI, OpenAI, SageMaker) for building and deploying AI solutions at scale.
- In-depth knowledge of software architecture principles, microservices architecture, containerization (e.g., Docker, Kubernetes), and distributed computing.
- A passion for Generative AI, and an understanding of strengths and weaknesses of Generative LLM's
- OWASP and Application security
- Strong proficiency in programming languages such as Python, R, Java, C# or Scala, with experience in frameworks like TensorFlow, PyTorch, scikit-learn, or Keras.
- Excellent problem-solving skills, analytical thinking, and attention to detail, with the ability to translate complex requirements into practical AI solutions.
- Strong communication and collaboration skills, with the ability to effectively interact with stakeholders across different levels of the organization.
- Relevant certifications (e.g., AWS Certified Solutions Architect, Google Cloud Certified - Professional Cloud Architect) are a plus.
- Experience in MLOps tools and frameworks (e.g., MLflow, Kubeflow, TensorFlow Extended).
- Expertise in conversational system architecture
- Knowledge of big data technologies
- Knowledge on Statistical Methods
- Knowledge on Linux / Unix Flavors.