Backend AI Engineer

San Francisco, CA - USA

Monthly Salary: Not Disclosed

Posted on: 2 days ago

Vacancies: 1 Vacancy

Job Summary

Job Description

Stefanini Group is hiring!

Stefanini is looking forBackend AI Engineer-Hybrid

For quick apply please contact Akash Gupta; Ph:

W2 Only!

Key Responsibilities:

Design develop and maintain robust backend services and APIs to support AI/ML applications across the organization.
Actively participate in Agile rituals and follow Scaled Agile processes as set forth by the CDP Program team.
Deliver high-quality backend services following Safe Agile Practices
Proactively identify and resolve issues with AI services APIs and model serving infrastructure.
Deploy comprehensive monitoring and alerting for backend AI systems implementing auto-remediation where possible to ensure system availability and reliability.
Employ a security-first testing and automation strategy adhering to backend engineering and MLOps best practices.
Collaborate with cross-functional teams including data scientists front-end engineers data engineers and business stakeholders to understand requirements and deliver robust backend solutions.
Keep up with the latest trends and technologies evaluating and recommending new tools frameworks and architectures to improve backend AI capabilities.

What Youll Bring:

Backend API Development (50%):

Design and develop robust scalable RESTful APIs and GraphQL services for AI/ML applications.
Build backend services for LLM-powered applications including RAG systems document processing pipelines and knowledge bases.
Implement secure API endpoints for model inference prompt orchestration and AI service integration.
Develop asynchronous processing workflows for long-running AI tasks (document analysis batch predictions).
Create middleware and service layers to abstract complex AI functionality for front-end consumption.
Design and implement caching strategies rate limiting and API versioning for production AI services.
Build event-driven architectures using message queues (SQS SNS EventBridge) for scalable AI workflows.
Ensure APIs meet security authentication and authorization requirements for Federal environments.
Implement comprehensive error handling logging and observability for AI services.

MLOps & Infrastructure (30%)

Build and maintain ML model serving infrastructure using AWS SageMaker Lambda and containerized deployments.
Integrate AWS AI services (Bedrock Textract Comprehend) into backend pipelines and APIs.
Develop CI/CD pipelines for automated testing deployment and rollback of AI services.
Implement model versioning A/B testing frameworks and canary deployment patterns.
Create data preprocessing and feature engineering pipelines using PySpark and Databricks.
Build orchestration workflows for multi-step AI processes (ingestion preprocessing inference post-processing).
Develop monitoring and alerting systems for model performance latency cost and availability.
Collaborate with data scientists to produce ML models and transition from prototype to production.
Implement vector databases and semantic search capabilities for RAG architecture.
Manage prompt templates model configurations and AI service parameters as code.

Performance & Support (20%)

Optimize backend performance for high-throughput AI workloads and real-time inference.
Monitor and troubleshoot production issues including latency errors and cost optimization.
Implement automated remediation and self-healing capabilities for backend services.
Conduct performance testing and capacity planning for AI infrastructure
Actively participate in Agile rituals and follow Scaled Agile processes as set forth by the CDP Program team.
Provide technical support and act as escalation point for backend AI service issues.
Create comprehensive technical documentation for APIs architecture patterns and deployment procedures.
Stay current on backend technologies AI infrastructure trends and Federal regulatory requirements.
Collaborate with security teams to ensure compliance with data protection and privacy regulations.

#LI-AG

#LI-HYBRID

Minimum Qualifications:

Education: Bachelors degree in Computer Science Software Engineering Information Systems or related technical field or equivalent experience
Experience: 4 years in backend development with at least 2 years building and deploying AI/ML or LLM-powered services.
Programming: Strong Python proficiency; experience with frameworks like FastAPI Flask or Django
API Design: Proven experience designing and implementing RESTful APIs with understanding of API security and best practices
LLM Integration: Hands-on experience building backend services for LLM applications including prompt orchestration RAG architectures and AI service integration
Cloud Platforms: Working knowledge of AWS services including Lambda API Gateway SageMaker Bedrock S3 and related AI/ML tools
Database Experience: Proficiency with both relational (PostgreSQL MySQL) and NoSQL databases (DynamoDB MongoDB); experience with vector databases (Pinecone Weaviate pgvector) preferred
Containerization: Experience with Docker and container orchestration (ECS EKS or similar)
ML Model Deployment: Demonstrated ability to deploy and serve ML models in production environments
Asynchronous Programming: Experience with async/await patterns message queues and event-driven architectures
Testing: Strong understanding of unit testing integration testing and test automation practices
Communication: Ability to collaborate effectively with cross-functional teams and translate business requirements into technical solutions

Preferred Qualifications:

3 years experience with PySpark and distributed computing frameworks
Experience with Databricks Collibra and Starburst
Knowledge of MLOps tools and frameworks (MLflow Kubeflow SageMaker Pipelines)
Experience with Infrastructure as Code (Terraform CloudFormation)
Familiarity with streaming data platforms (Kafka Kinesis)
Experience building end-to-end data pipelines and ETL processes
Understanding of microservices architecture and service mesh patterns
Experience with observability tools (DataDog New Relic CloudWatch)
Background working in regulated industries (financial services healthcare government)
Knowledge of data governance lineage and compliance frameworks
Experience with GraphQL API design and implementation
Familiarity with econometric models and statistical computing environments (R Stata)

Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We also speak with you about the process including interviews and job offers.

About Stefanini Group:

The Stefanini Group is a global provider of offshore onshore and near shore outsourcing IT digital consulting systems integration application and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas Europe Africa and Asia and more than four hundred clients across a broad spectrum of markets including financial services manufacturing telecommunications chemical services technology public sector and utilities. Stefanini is a CMM level 5 IT consulting company with a global presence. We are CMM Level 5 company

Required Experience:

Job DescriptionStefanini Group is hiring!Stefanini is looking forBackend AI Engineer-HybridFor quick apply please contact Akash Gupta; Ph: W2 Only!Key Responsibilities:Design develop and maintain robust backend services and APIs to support AI/ML applications across the organization.Actively particip...