Staff Software Engineer - Applied AI

CVS Health•Work At Home-Ohio, OH

4d•$118,450 - $236,900

About The Position

CVS Health is looking for a Staff Software Engineer - Applied AI, who isn’t afraid to use all their knowledge and communication skills to tackle complex problems. Our ideal candidate is detail-oriented and able to collaborate on the improvement of our software and systems. You will be involved in the structural design process, estimating costs, and performing quality control throughout the stages of implementation. A first-class Staff Engineer will be someone whose engineering expertise translates into streamlined and cost-effective processes. To ensure success as a Staff Software Engineer - Applied AI with a focus on applied AI solutions, you should demonstrate specialized engineering knowledge and experience while designing, providing guidance, and implementing solutions to complex problems. You will work with business, information, and technology teams to recommend and implement technology solutions needed to enable leading-edge capabilities and develop comprehensive patterns that outline how those capabilities get realized in response to evolving business needs.

Requirements

7+ years of experience in large scale software development.
5+ years of solution design and/or architecture experience, including capturing requirements in a customer-facing capacity.
5+ years of experience in designing and developing solutions using NodeJS, highly scalable microservices, REST APIs.
3+ years of experience in AWS technology stack and DevOps/CICD processes.
3+ years collaborating with engineering teams on prototype development.
Experience with AWS Bedrock and AI technologies.
Expertise in Python programming for AI/ML development.

Nice To Haves

Excellent collaboration and communication skills required to ideate solutions that are sufficient and feasible to both the business leads and the technical teams.
Exceptional organizational, analytical, problem-solving, strategic thinking, and time management abilities.
Experience with optimization skills to improve performance, scalability, and usability of our applications.
Ability to develop technical briefs and detailed solution designs.
Extensive knowledge of engineering processes, structural design, and system optimization.
Experience with agile development, SAFe Agile experienced preferred.
Direct, hands-on experience architecting and building production solutions specifically using AWS Bedrock, the Converse API, Bedrock Agents, and Bedrock Knowledge Bases.
Relevant AWS Certifications are a bonus (e.g., AWS Certified Machine Learning - Specialty, AWS Certified Solutions Architect - Professional, AWS Certified AI Practitioner).

Responsibilities

Lead the end-to-end design, development, testing, deployment, maintenance, and enhancement of highly scalable, reliable, and secure AI services and applications utilizing AWS Bedrock (including Foundation Models, Knowledge Bases, Agents), the Converse API, AWS SageMaker, AWS Lambda, Amazon S3, and other relevant AWS AI/ML and core services.
Architect robust, efficient, and secure AI/ML computing infrastructures and application stacks capable of handling large-scale data processing and inference demands.
Design and implement solutions leveraging the AWS Bedrock Converse API for unified interaction with foundation models, incorporating advanced features like tool calling and multimodal input processing (text, image, documents).
Develop and implement Retrieval-Augmented Generation (RAG) patterns using AWS Bedrock Knowledge Bases, integrating proprietary data from sources like Amazon S3 and leveraging vector databases to enhance model relevance and accuracy.
Build comprehensive solutions that effectively integrate Bedrock's managed services with custom components, such as AWS Lambda functions for implementing Bedrock Agent actions or custom data processing logic.
Actively research, evaluate, and stay current with the latest advancements, trends, and research in AI/ML, particularly in generative AI, foundation models, large language models (LLMs), and evolving AWS capabilities.
Champion and implement responsible AI practices, ensuring fairness, transparency, security, and ethical considerations are integrated throughout the development lifecycle, potentially leveraging tools like AWS Bedrock Guardrails.
Collaborate with cross-functional teams, including product managers, architects, and software developers, to define technical requirements and create robust and scalable architectures that meet business objectives.
Mentor and guide junior engineers, helping them enhance their technical skills and grow professionally through knowledge-sharing activities, technical training, and fostering a culture of learning within the team.