AI/ML Engineer

Primary Responsibilities:

• Develop, and operate secure cloud platform services and software that meet business requirements
• Create GitHub Actions and workflows for standardizing CI/CD pipelines within UHG
• And ensure that pipelines are following best practices, documented and delivered in a scalable reusable manner
• Automate repetitive tasks (TOIL), monitor applications, simplify work practices, define metrics, and ensure the operational quality of applications
• Manage security controls at the platform level to enable secure, efficient, and policy-compliant operations
• Collaborate with multiple partner teams to communicate information security guidance and standards and reduce information security risks
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

                  AI User Responsibilities:

• Uses GitHub Copilot to speed up the creation of boilerplate code
• Uses M365 Copilot to recap meetings and draft emails
• Uses a chat-based AI tool to debug code
• Uses GenAI to create sample test data or test cases
• Uses StoryCraft to streamline the creation of user stories

 

Required Qualifications:

• BS or higher in Computer Science or similar experience
• 3+ years of experience as a software development engineer or equivalent hands-on experience producing code for production systems
• 1+ years of engineering experience in building infrastructure using code and repeatable designs (IaC)
  1+ years of experience in designing, building and deploying ML models with AWS SageMaker or Azure ML
• 2+ years of experience working with Agile team
• 1+ years’ experience using AI tools to enhance productivity and innovation, such as GitHub CoPilot
• Experience in automating CI/CD using Jenkins [Pipeline as Code], GitHub actions, or similar tools, along with proficiency in source control systems such as Git
• Experience working with Public Cloud providers such as AWS, Azure, GCP, beyond basic IaaS functionality
• Experience with using and deploying LLMs
• Proficient in Python and Familiarity with python tools for data processing

 

Preferred Qualifications:

• Experience with containers and orchestration platforms, such as Kubernetes
• Experience with Cloud Computing (AWS/Azure/GCP), DevOps tools and automation using Python or any other scripting language
  Experience using instrumentation, logging, and tracing tools (Prometheus, CloudWatch, Stack Driver, Azure Monitor, etc.)
• Knowledge of API design and lifecycle management (REST, etc.)
• Knowledge in data storage, caching, and optimization (SQL and NoSQL databases)
• Familiarity with inter-service messaging and stream discovery (SQS, Pub/Sub Kafka, etc.)
• Proven excellent verbal, written and interpersonal communication skills
• Proven design mindset with the ability to construct scalable, distributed services

 

AI Expectation:

• Working with Generative AI API’s and Frameworks
• Hands-on experience with API’s like OpenAI, Google Gemini and Hugging face
• Experience in using Tools like GitHub Copilot, Cursor, Windsurf or Amazon Code Whisperer etc.
• Good understanding of LLMs and generative models
• Familiarity with frameworks like Lang Chain, AutoGen and Microsoft Copilot Studio etc.
• Prompt Engineering
• How to effectively create prompts to get desired output from generative models