Key skills
AWSAzureCloudDistributed SystemsDockerKubernetesMicroservicesPythonTerraformAIMLGenAILarge Language ModelsRAGLangChainAgenticLangGraphCI/CD
About this role
Role Overview
- Develop and implement GenAI applications leveraging: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, Prompt engineering techniques, Agentic AI concepts and workflows
- Build intelligent pipelines using frameworks such as LangChain, LangGraph, and Microsoft Foundry Agent Service
- Evaluate solution performance, accuracy, and scalability of GenAI implementations
- Contribute to the end-to-end GenAI lifecycle, including: Solution design and development, Integration and deployment, Performance tuning and optimization
- Support secure deployment, horizontal scaling, and operational stability of GenAI workloads
- Assist in implementing monitoring, logging, and observability practices for production environments
- Develop and deploy GenAI systems across cloud platforms (Azure and AWS)
- Contribute to distributed system design for scalable AI workloads
- Utilize modern infrastructure practices: Containerization (Docker), Orchestration (Kubernetes), Infrastructure as Code (Terraform, ARM/Bicep)
- Ensure solutions meet enterprise expectations for availability, performance, and security
- Develop scalable applications using Python and microservices-based architectures
- Apply secure coding standards and proper data handling practices for enterprise, regulated environments
- Contribute to CI/CD pipelines, automated testing, and deployment workflows
- Participate in code reviews and adhere to engineering best practices
Requirements
- Bachelor’s degree, or equivalent work experience
- Three to five years of relevant experience
- Bachelor’s degree in Computer Science, Engineering, or related field
- 5–8 years of experience in software or platform engineering
- 2+ years hands-on experience with GenAI systems, including LLMs and RAG architectures and vector databases
- Understanding of agentic AI concepts and exposure to frameworks such as LangChain or LangGraph
- Experience with cloud platforms (Azure and/or AWS)
- Knowledge of distributed systems and scalable application design
- Proficiency in Python development
- Experience with Docker, Kubernetes, and Infrastructure as Code tools
- Experience deploying GenAI or ML solutions in production environments
- Familiarity with observability and monitoring tools
- Understanding of AI governance, compliance, and security practices
- Experience in financial services or other regulated industries is a plus
Tech Stack
- AWS
- Azure
- Cloud
- Distributed Systems
- Docker
- Kubernetes
- Microservices
- Python
- Terraform
Benefits
- Healthcare (medical, dental, vision)
- Basic term and optional term life insurance
- Short-term and long-term disability
- Pregnancy disability and parental leave
- 401(k) and employer-funded retirement plan
- Paid vacation (from two to five weeks depending on salary grade and tenure)
- Up to 11 paid holiday opportunities
- Adoption assistance
- Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law