Technical Architect - AWS & Machine Learning at fa-etqd-saasfaprod1 in United States
- Company: fa-etqd-saasfaprod1
- Location: United States
- Posted: Sep 19, 2026
- Type: Full-time
- Salary: $81,978 to $160,020
- Experience: 5+ years
Overview
We are seeking a hands-on Technical Architect to lead the design and implementation of cloud-native applications, distributed systems, and machine learning infrastructure within AWS. This individual will play a key role in defining technical architecture, guiding development teams, and delivering sc…
Job description
- We are seeking a hands-on Technical Architect to lead the design and implementation of cloud-native applications, distributed systems, and machine learning infrastructure within AWS. This individual will play a key role in defining technical architecture, guiding development teams, and delivering scalable solutions that support AI/ML-driven business capabilities.
- The ideal candidate combines deep AWS expertise, software engineering experience, and significant hands-on experience with Amazon SageMaker and production machine learning deployments. Experience supporting NLP, embeddings, and AI-powered applications is highly desirable.
Responsibilities
- Design and implement scalable, secure, and highly available solutions within AWS.
- Architect machine learning-enabled applications leveraging Amazon SageMaker for model deployment, inference, endpoint management, and integration with downstream services.
- Define architecture patterns and best practices for distributed, event-driven applications.
- Lead the technical design and implementation of cloud-native services utilizing AWS Lambda, SNS/SQS, EventBridge, DynamoDB, Amazon SageMaker Endpoints, Amazon Bedrock.
- Collaborate closely with software engineers, data scientists, and product teams to operationalize machine learning solutions and AI-driven workflows.
- Contribute hands-on development using Python for application services, automation, machine learning integrations, and SageMaker-based processing solutions.
- Ensure machine learning workloads are scalable, reliable, secure, and cost-effective.
Requirements
- Design and implement scalable, secure, and highly available solutions within AWS.
- Architect machine learning-enabled applications leveraging Amazon SageMaker for model deployment, inference, endpoint management, and integration with downstream services.
- Define architecture patterns and best practices for distributed, event-driven applications.
- AWS Lambda
- SNS/SQS
- EventBridge
- DynamoDB
- Amazon SageMaker Endpoints
- Amazon Bedrock
- Collaborate closely with software engineers, data scientists, and product teams to operationalize machine learning solutions and AI-driven workflows.
- Contribute hands-on development using Python for application services, automation, machine learning integrations, and SageMaker-based processing solutions.
- Ensure machine learning workloads are scalable, reliable, secure, and cost-effective.
- 5+ years of experience in software engineering, cloud engineering, technical architecture, or a related discipline.
- Strong experience designing and implementing AWS-based solutions in production environments.
- Hands-on experience with Amazon SageMaker, including model deployment, endpoint management, inference workflows, and integration with enterprise applications.
- Experience supporting production machine learning workloads within AWS environments.
- Lambda
- SNS/SQS
- EventBridge
- DynamoDB
- SageMaker
- Experience building and supporting highly scalable distributed systems.
- Strong understanding of asynchronous processing and event-driven architectures.
- Terraform
- Python
- GitHub Actions
- CI/CD automation
- Ability to balance architectural design responsibilities with hands-on technical implementation.
- Experience deploying and managing NLP, embedding, and generative AI solutions using Amazon SageMaker.
- Understanding of embedding models, vectorization techniques, semantic search, and retrieval-based AI architectures.
- Experience implementing OCR and document-processing workflows utilizing machine learning services.
- Experience integrating SageMaker-hosted models into production applications and distributed architectures.
- Familiarity with MLOps concepts, model lifecycle management, monitoring, and AI application deployment best practices.
- Experience implementing AI/ML solutions using Amazon Bedrock or similar generative AI platforms.
- Familiarity with Retrieval-Augmented Generation (RAG) architectures and vector databases.
Skills
Required
- AWS
- Amazon SageMaker
- Python
- Terraform
- GitHub Actions
- CI/CD automation
- Distributed systems
- Event-driven architecture
- Asynchronous processing
- Lambda
- SNS/SQS
- EventBridge
Preferred
- NLP
- Embedding models
- Vectorization techniques
- Semantic search
- Retrieval-based AI architectures
- OCR
- Document-processing workflows
- MLOps
Benefits
- The salary range for this position takes into consideration a variety of factors, including but not limited to skill sets, level of experience, applicable office location, training, licensure and certifications, and other business and organizational needs. The new hire salary range displays the minimum and maximum salary targets for this position across all US locations, and the range has not been adjusted for any specific state differentials. It is not typical for a candidate to be hired at or near the top of the range for their role, and compensation decisions are dependent on the unique facts and circumstances regarding each candidate. A reasonable estimate of the current salary range for this position is $81,978 to $160,020. Please note that the salary range posted reflects the base salary only and does not include benefits or any potential variable compensation programs. Information regarding the benefits available for this position are in our benefits overview.
About fa-etqd-saasfaprod1
At Perficient, we promise to challenge, champion, and celebrate our people. You will experience a unique and collaborative culture that values every voice. Join our team, and you’ll become part of something truly special. We believe in developing a workforce that is as diverse and inclusive as the clients we work with. We’re committed to actively listening, learning, and acting to further advance our organization, our communities, and our future leaders… and we’re not done yet. Perficient, Inc. proudly provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a protected veteran in accordance with applicable federal, state and local laws. Perficient, Inc. complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Perficient, Inc. expressly prohibits any form of unlawful employee harassment based on race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or covered veterans. Improper interference with the ability of Perficient, Inc. employees to perform their expected job duties is absolutely not tolerated.