Overview
On Site
Contract - W2
Skills
SQL
Jenkins
python
GitHub
QA
API
Kubernetes
Data Science
deployment
machine learning
ECS
logging
TERRAFORM
Best Practices
authentication
use cases
Continuous Integration/Delivery
Application Architecture
estimation
Level Design
Microservice
Mentor
API Gateway
Amazon Web Services
Continuous Improvement
Datasets
AWS CodePipeline
Data Sources
OpenShift
AWS Cloudwatch
Prometheus
Real-Time
Telemetry
Packaging
Job Details
Job Responsibilities:
- Understand the Business End to End.
- Understand the Application Architecture.
- Responsible for Designing and building Applications.
- Understand the project timelines and deadlines.
- Provide Impact analysis for new requirements or changes.
- Responsible for low level design with the team.
- Convey architectural solutions to all levels of professionals and leaders.
- Ensure Code Quality and Deliverables.
- Lead the team and deliverables -Prioritize work with stakeholders.
- Understand and follow the current Code Build and Deployment patterns across all environments.
- Perform checkouts of the code deployments before the QA starts testing.
- Support continuous improvement, investigating alternatives and technologies, and presenting for architectural review.
- Develop and Mentor Junior Developers.
- Plan and prepare to support PI planning Events.
- Work breakdown by stories for development.
- Accurate work Estimation and commitment to timelines and deadlines.
- Identify dependencies and communication.
Skills and Experience Required:
Required
- Expert-level Python development with a focus on production-grade microservices
- Proficient in Python dependency management and packaging for scalable services
- Strong experience in structured logging, exception handling
- Experience with observability using tools like CloudWatch, Open Telemetry, Prometheus, or others
- Deep familiarity with OpenAI APIs (chat/completions, function calling, embeddings)
- Experience designing multi-agent architectures, where each agent handles distinct data sources or functional areas
- Data Science & ML Skills
- Ability to query, aggregate, understand, and potentially augment large datasets using platforms like Databricks, PySpark, or SQL
- Practical experience in using machine learning and rule-based logic to identify trends or classify behavior
- Familiarity with RAG architecture and vector similarity search using tools like FAISS, pgvector, or Pinecone
- Familiarity with FastAPI, LangChain, or similar frameworks for GenAI orchestration
Desired
- Expertise in integrating and orchestrating multiple backend APIs, including dynamic payload creation and conditional routing logic
- Proficient in implementing OAuth2 with JWT for secure API authentication and service-to-service communication
- Strong understanding of security best practices for sensitive data handling
- Cloud & Deployment Skills
- Experience with AWS services (Lambda, ECS, API Gateway, S3, Secrets Manager, Bedrock, SageMaker) or other cloud providers
- Experience with OpenShift or Kubernetes for deploying and scaling containers
- Familiar with CI/CD pipelines using GitHub Actions, Jenkins, or AWS CodePipeline
- Knowledge of infrastructure-as-code using Terraform, Helm, or similar tools
- Prior work with intelligent Gen AI assistants or in-app AI integration use cases
- Experience building event-driven systems or real-time insights dashboards.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.