Senior Serverless And Generative AI Engineer

Job Description

Job DescriptionJob Description:

• The Senior Serverless & Generative AI Engineer is responsible for designing and building scalable, event-driven, serverless applications on AWS while integrating Generative AI and document intelligence capabilities.
• This role focuses on architecting resilient APIs, asynchronous workflows, AI-powered extraction pipelines, and human-in-the-loop validation systems.
• The ideal candidate brings deep AWS serverless expertise, strong API and event modeling experience, and hands-on integration of large language models and document processing systems in production environments.

Core AWS Serverless Platform:

• Develop and optimize AWS Lambda functions using Node.js or Python, including cold start optimization, memory tuning, and concurrency management.
• Design and manage API Gateway REST and HTTP APIs including routing, authorization, request/response transformations, throttling, and caching.
• Build event-driven architectures using EventBridge, SNS, and SQS with retry semantics, dead-letter queues, and delivery guarantees.
• Orchestrate workflows using AWS Step Functions (Standard and Express) for multi-step and long-running processes.
• Implement storage solutions using Amazon S3 including lifecycle policies, versioning, pre-signed URLs, and performance considerations.
• Design persistence layers using DynamoDB (single-table design, GSIs, transactions) and/or RDS (PostgreSQL/MySQL) based on application requirements.
• Implement secure IAM policies, resource-based access controls, KMS encryption, and least-privilege security models.

Generative AI, ML, and Document Extraction:

• Integrate large language models and generative AI APIs such as OpenAI, Anthropic, AWS Bedrock, or self-hosted models.
• Design cost-efficient and secure prompt strategies including batching, caching, and safety controls.
• Implement OCR and document extraction solutions using tools such as AWS Textract, Tesseract, or Intelligent Document Processing platforms.
• Apply structured information extraction techniques including prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and vector similarity search.
• Design canonical schemas, entity extraction pipelines, schema mapping, validation, and transformation workflows.

API Design and Eventing:

• Design RESTful and/or GraphQL APIs with best practices including versioning, pagination, idempotency, and structured error handling.
• Implement spec-driven development using OpenAPI or AsyncAPI.
• Design idempotent operations, concurrency control, optimistic locking, and sequence guarantees where required.
• Model domain events with proper contracts, versioning, and durable event-driven delivery using EventBridge, SNS/SQS, or Kafka.

Frontend and Human-in-the-Loop Tools:

• Develop frontend solutions using React and TypeScript for validation dashboards and review workflows.
• Design human-in-the-loop experiences including approve/reject workflows, confidence indicators, diff comparisons, and bulk validation tools.
• Implement micro frontend architectures for independently deployable UI components.
• Integrate analytics and visualization tools for monitoring accuracy, error rates, and model drift.

Observability, Reliability, and Security:

• Implement monitoring and tracing using CloudWatch, X-Ray, OpenTelemetry, and structured logging.
• Build dashboards and alerts aligned to SLOs and error budgets.
• Develop automated testing strategies including unit, integration, and contract testing.
• Implement CI/CD pipelines using GitHub Actions and Infrastructure as Code with CloudFormation or CDK.
• Ensure security best practices including encryption at rest and in transit, secrets management, input validation, rate limiting, and OWASP compliance.
• Optimize cloud costs across Lambda, S3, DynamoDB, and API Gateway usage.

Engineering Practices and Collaboration:

• Implement infrastructure as code using AWS CloudFormation or CDK for reproducible deployments.
• Apply API contract testing and schema validation using OpenAPI and JSON Schema.
• Collaborate closely with Product, ML, and QA teams to iterate on extraction models and validation workflows.

Requirement/Must Have:

• Strong hands-on experience with AWS serverless architecture and event-driven systems.
• Experience integrating generative AI and large language model APIs into production systems.
• Deep understanding of API design, event modeling, and distributed systems.
• Experience with DynamoDB and/or relational database design patterns.
• Strong understanding of observability, CI/CD, and secure cloud architecture.

Should Have:

• Experience with Retrieval-Augmented Generation and vector search systems.
• Experience building human-in-the-loop validation platforms.
• Experience with analytics and visualization tools such as Power BI or Tableau.
• Strong collaboration and cross-functional communication skills.

Qualification and Education:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field preferred.
• Extensive experience in serverless architecture, AI integration, and scalable cloud platform engineering required.

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading staffing and recruiting powerhouse. Proudly recognized as a nationally and locally certified diversity firm, Cynet delivers agile, scalable talent solutions across industries. With an active footprint in all 50 U.S. states and Canada, we support thousands of consultants through our expansive, high-performing recruitment engine operating across North America and Asia—ensuring speed, quality, and consistency in every hire.