Automation & AI Engineer

🔥 0 minutes ago

🏛️ District of Columbia, Washington – Remote

🏛️ District of Columbia – Remote ☕ Washington – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🤖 AI Engineer

👻 Ghost score 10%

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SAIC

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1969

☁️ SaaS

📣 Marketing

🏢 Enterprise

💰 $500M Post-IPO Debt - SAIC on 2025-09

SaaS • Marketing • Enterprise

SAIC is represented in the supplied content by marketing and product copy that matches Bitly — a cloud-based link management and QR-code platform. The material describes a SaaS offering for URL shortening, dynamic QR Codes, link analytics, mobile-friendly landing pages, branded links, UTM campaign tracking, digital business cards, developer APIs and AI-enhanced features. It targets marketers, developers, and enterprises across industries (retail, CPG, hospitality, media, healthcare, finance, education) and emphasizes integrations, analytics, and enterprise-grade capabilities. Note: the provided text appears to be Bitly’s website content rather than information about SAIC; if you intended the defense/technology firm SAIC (Science Applications International Corporation), please provide relevant content.

📋 Description

• Modernize GMF and related legacy workloads by refactoring monoliths and batch processes into secure, cloud-native architectures with embedded AI/automation • Design, build, and deploy LLM- and agentic AI-based solutions using technologies such as LangChain, LangGraph, RAG, vector search, and AWS Bedrock agents • Automate complex workflows and integrate solutions with IRS 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 requirements in a regulated federal financial environment

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field • Ability to obtain and maintain a public trust requiring U.S. Citizenship or Green Card • 9+ years in software, ML, or data engineering, including experience with application modernization • 4+ years building and deploying 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 such as LangChain and LangGraph • Proficiency in Python and common ML/NLP libraries such as Hugging Face, Transformers, scikit-learn, PyTorch/TensorFlow • Production experience with AWS, including networking/IAM, Lambda, ECS/EKS, API Gateway, S3, DynamoDB, RDS, OpenSearch, SageMaker, and CloudWatch • Practical experience using AWS Bedrock for LLM-powered applications and agents, including knowledge bases and guardrails • Experience implementing RAG and working with vector search/databases • Experience with CI/CD and infrastructure-as-code such as Terraform or CloudFormation • Familiarity with MLOps/AIOps such as MLflow or SageMaker and AI-focused observability • Strong SQL skills and experience integrating legacy data into modern platforms • Experience with Docker and container orchestration such as Kubernetes or AWS ECS/EKS • Desired: Experience with Databricks, LangSmith or similar tools, CrewAI, AutoGen, Temporal, Model Context Protocol, BrainTrust, DeepEval, or similar frameworks