AI Engineer

What you’ll deliver

You will build and deploy multi-model, agentic workflows that can dynamically select the right model based on task context, cost, and latency. You will also implement RAG pipelines and develop backend and API layers that enable low-latency AI responses, along with tools for monitoring and improving data quality, latency, and observability.

Responsibilities

• Translate product requirements and user stories into production-grade AI solutions using AWS Bedrock, Lambda, ECS/EKS, and Databricks.
• Implement RAG pipelines using Delta tables, Unity Catalog, and Vector Search.
• Design and deploy multi-model agents that select between models such as Claude, GPT, Llama, Titan, and others based on task context, cost, and latency.
• Implement multi-agent orchestration frameworks for collaboration among specialized agents (for example: data retriever, planner, summarizer, and action executor) for complex construction workflows.
• Own the full delivery lifecycle including design, development, testing, deployment, monitoring, and maintenance.
• Build APIs, backend services, and agentic workflows using Python, FastAPI, LangChain, and AWS SDKs.
• Create reusable connectors and orchestration layers for multi-model agents across platforms such as Claude, GPT, and Llama.
• Develop front-end integrations for Teams and web SPAs using REST or GraphQL endpoints.
• Partner with Data Engineering to design robust ETL/ELT pipelines from enterprise systems to the Databricks Lakehouse.
• Ensure efficient data access, caching, and vectorization to support low-latency AI response.
• Build tools to monitor and improve data quality, latency, and observability.
• Use Terraform, AWS CDK, and GitHub Actions to automate infrastructure and deployments.
• Implement LLMOps practices including cost monitoring, latency optimization, usage analytics, and model versioning.
• Enforce security, governance, and access standards aligned with enterprise policies.
• Collaborate with product managers, site AI engineers, and data scientists to iterate in Agile sprints.
• Communicate technical progress clearly to non-technical stakeholders and contribute to internal AI playbooks and templates.

Requirements

• 4-6 years of professional software development experience on AWS, with 2+ years focused on AI/ML engineering (LLMs, RAG, Bedrock, or similar).
• Strong coding proficiency in Python (LangChain, FastAPI, boto3) and solid experience with SQL, Databricks, and vector databases.
• Experience designing and deploying production systems using AWS Lambda, ECS/EKS, API Gateway, Step Functions, S3, CloudFront, and KMS.
• Strong foundation in CI/CD, IaC (Terraform/CDK), and GitHub Actions.
• Experience training, retraining, and transfer learning on ML models is desirable.
• Bachelor’s degree in Computer Science, Engineering, Physics, or a related field; Master’s preferred.
• Prior hands-on work in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
• Excellent collaboration and communication skills, with the ability to work cross-functionally.
• Integration & ETL skills including foundational understanding of ETL/ELT design, Airflow or Databricks Workflows, and REST/GraphQL API development, plus proven collaboration with Data Engineering on source-to-lake and lake-to-agent pipelines.

Technologies you’ll work with

AWS Bedrock, AWS Lambda, ECS, EKS, Databricks, Delta tables, Unity Catalog, Vector Search, Claude, GPT, Llama, Titan, Python, FastAPI, LangChain, AWS SDKs, boto3, SQL, vector databases, API Gateway, Step Functions, S3, CloudFront, KMS, Terraform, AWS CDK, GitHub Actions, CI/CD, LLMOps, ETL/ELT, Airflow, Databricks Workflows, REST, GraphQL

Benefits

• Competitive salaries
• Auto allowances and gas cards for certain roles
• Market leading medical and emotional and mental health benefits
• Dental and vision insurance plans
• Virtual care options for physical therapy and primary care
• Generous paid time off
• 401k plan with employer match
• Access to expert financial resources
• Company paid and voluntary life insurance
• Tax deferred savings accounts
• 10 backup daycare days each year
• Short- and long-term disability
• Commuter benefits

Working conditions

• Regularly required to sit for long periods of time; talk or hear; perform fine motor skills using a keyboard, telephone, or writing.
• Frequently required to stand, walk, and reach with arms and/or hands.
• Specific vision abilities include close vision, distance vision, depth perception, and ability to adjust focus.
• Office environment with quiet to moderate noise level.
• Job site walking.

Equal Employment Opportunity

Suffolk provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, pregnancy or maternity, national origin, citizenship, genetic information, disability, protected veteran, gender identity, age or any other status protected by law. This policy applies to recruiting, hiring, transfers, promotions, terminations, compensation, benefits, and all other terms and conditions of employment. Suffolk will not tolerate any unlawful discrimination toward, or harassment of, applicants or employees by anyone at Suffolk, or anyone working on behalf of Suffolk.

Compensation information

• Where required by law, pay ranges can be found in Suffolk’s job postings.
• Base salary is one component of Suffolk’s total rewards package.
• Actual salaries may be based on skill set, experience, education, and other qualifications.
• Suffolk offers a comprehensive benefits package as part of its overall total rewards strategy.
• Salary ranges are reviewed regularly to reflect market trends.