AI & Cloud Modernization Engineer

SAIC; Richmond (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

SAIC is seeking an Automation & AI Engineer to modernize legacy systems into intelligent, secure, cloud-native applications for a federal environment. You will collaborate with AI engineers, developers and testers to design scalable, secure AI-driven modernization solutions and integrate legacy data sources into modern platforms.

The role emphasizes hands-on work with LLM frameworks, AWS Bedrock, and MLOps practices to ensure robust security, governance, and observability within a high-value

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field (4 years experience in lieu of degree).
• Ability to obtain and maintain a public trust requiring U.S. Citizenship or Green Card.
• 0+ years in software, ML, or data engineering, including experience with application modernization.
• Familiar with AI/ML or LLM-based applications in production.
• Strong experience with modern application architectures (microservices, REST APIs, event-driven) and legacy integration.
• Hands-on experience building agentic AI solutions using LLM frameworks (e.g., LangChain, LangGraph).
• Proficiency in Python and common ML/NLP libraries (e.g., Hugging Face, Transformers, scikit-learn, PyTorch/TensorFlow).
• Production experience with AWS (networking/IAM, Lambda, ECS/EKS, API Gateway, S3, DynamoDB, RDS, OpenSearch, SageMaker, CloudWatch).
• Practical experience using AWS Bedrock for LLM-powered applications and agents (knowledge bases, guardrails).
• Experience implementing RAG and working with vector search/databases.
• Experience with CI/CD and infrastructure-as-code (e.g., Terraform, CloudFormation).
• Familiarity with MLOps/AIOps (e.g., MLflow, SageMaker) and AI-focused observability (logging, metrics, drift/quality monitoring) for LLM/agent workflows.
• Strong SQL skills and experience integrating legacy data into modern platforms.
• Experience with Docker and container orchestration (Kubernetes, AWS ECS/EKS).

Responsibilities

• Modernize legacy workloads by refactoring monoliths into secure, cloud-native architectures (microservices, APIs, event-driven) with embedded AI/automation.
• Design, build, and deploy LLM- and agentic AI–based solutions that automate complex workflows and integrate with data sources.
• Implement platform engineering and MLOps/AIOps best practices, including CI/CD, infrastructure-as-code, model/prompt lifecycle management, and responsible AI controls.
• Collaborate with architects, developers, testers, and stakeholders to design scalable, secure AI-driven modernization solutions.
• Integrate legacy data sources into modern data platforms and AI-enabled services.
• Ensure compliance with security, privacy, and governance in a regulated federal financial environment.

Skills

Python

LLM frameworks

AWS

Kubernetes

CI/CD

MLOps

Data integration

SQL

REST APIs

Education

Bachelor’s degree in Computer Science or related field

Tools

LangChain

LangGraph

Terraform

CloudFormation

Docker

SageMaker

Job description

SAIC is seeking an Automation & AI Engineer to modernize legacy systems into intelligent, secure, cloud-native applications for a federal environment. You will collaborate with AI engineers, developers and testers to design scalable, secure AI-driven modernization solutions and integrate legacy data sources into modern platforms.

The role emphasizes hands-on work with LLM frameworks, AWS Bedrock, and MLOps practices to ensure robust security, governance, and observability within a high-value