Senior AI Engineer

Quick Facts

• Role: Senior AI Engineer

Description

Own end-to-end delivery of production AI solutions, including RAG pipelines and multi-model/multi-agent systems deployed on AWS. Build backend services and agentic workflows, create reusable connectors and orchestration layers, and integrate AI capabilities into web and Microsoft Teams experiences. Partner on ETL/ELT data pipelines and implement LLMOps, monitoring, security, and governance for reliable enterprise AI.

Responsibilities

• Translate product requirements and user stories into production-grade AI solutions using AWS Bedrock, Lambda, ECS/EKS, and Databricks

• Implement RAG pipelines with Delta tables, Unity Catalog, and Vector Search

• Design and deploy multi-model agents that dynamically select between LLMs based on task context, cost, and latency

• Implement multi-agent orchestration frameworks for complex construction workflows

• Own full lifecycle delivery: design, development, testing, deployment, monitoring, and maintenance

• Build APIs and backend services/agentic workflows with Python, FastAPI, LangChain, and AWS SDKs

• Create reusable connectors and orchestration layers for multi-model agents

• Develop front-end integrations for Teams and web SPAs via REST or GraphQL endpoints

• Partner on ETL/ELT pipelines from enterprise systems to the Databricks Lakehouse

• Ensure efficient data access, caching, and vectorization for low-latency AI responses

• Build tools to monitor and improve data quality, latency, and observability

• Automate infrastructure and deployments with Terraform, AWS CDK, and GitHub Actions

• Implement LLMOps: cost monitoring, latency optimization, usage analytics, and model versioning

• Enforce security, governance, and access standards

• Collaborate in Agile sprints and communicate technical progress to non-technical stakeholders

Requirements

• 5+ years of professional software development experience on AWS, with 2+ years focused on AI/ML engineering (LLMs, RAG, Bedrock, or similar)

• Strong Python proficiency (LangChain, FastAPI, boto3) plus solid SQL experience, Databricks, and vector databases

• Experience designing and deploying production systems using AWS Lambda, ECS/EKS, API Gateway, Step Functions, S3, CloudFront, and KMS

• Strong CI/CD foundation and IaC experience (Terraform/CDK) with GitHub Actions

• Bachelor’s degree in Computer Science/Engineering/Physics or related field (Master’s preferred)

• Excellent cross-functional collaboration and communication skills

• Integration/ETL fundamentals, including Airflow or Databricks Workflows, and REST/GraphQL API development

• Proven collaboration with Data Engineering on source-to-lake and lake-to-agent pipelines

Benefits

• Comprehensive benefits package including competitive salaries and medical/mental health benefits

• Dental and vision insurance

• Virtual care options for physical therapy and primary care

• Generous paid time off

• 401k plan with employer match

• Company paid and voluntary life insurance and tax-deferred savings accounts

• Backup daycare days, short- and long-term disability, commuter benefits, and more