Automation & AI Engineer

Job ID: 2617370 **Location:** Washington, DC, US **Date Posted:** 2026\-09\-29 **Category:** Software **Subcategory:** SW Engineer **Schedule:** Full\-Time **Shift:** Day Job **Travel:** No **Minimum Clearance Required:** None **Clearance Level Must Be Able to Obtain:** Public Trust **Potential for Remote Work:** ORA\_REMOTE **Description** SAIC is seeking a self\-motivated, customer\-focused **Automation \& AI Engineer** to join our team. You will work with AI Engineers, Developers, and Testers to modernize legacy systems into intelligent, secure, cloud\-native applications. You will help design and enhance a highly secure system for a federal agency that processes high\-value financial transactions over the Internet. Experience with payment systems, trading systems, or other highly secure transactional environments is a strong plus. This role is ideal for someone who enjoys solving complex problems with modern AI and cloud technologies in a collaborative team environment. **Key Responsibilities** * Modernize GMF and related legacy workloads by refactoring monoliths and batch processes into secure, cloud\-native architectures (microservices, APIs, event\-driven systems) with embedded AI/automation. * Design, build, and deploy LLM\- and agentic AI–based solutions (e.g., LangChain, LangGraph, RAG, vector search, AWS Bedrock agents) that automate complex workflows and integrate 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. **Qualifications** **Required** * 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 (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). **Desired** * Strong technical judgment and communication skills; able to explain AI modernization approaches to technical and business stakeholders. * Experience with **Databricks** (notebooks, Delta Lake, ML/feature store) for data and ML pipelines. * Experience with LLM/agent observability and debugging tools (e.g., **LangSmith** or similar). * Experience with advanced agent frameworks (e.g., **CrewAI**, **AutoGen**) and multi\-agent workflows. * Hands\-on experience operating agents in production (safety/guardrails, performance tuning, lifecycle management). * Experience with durable workflow engines (e.g., **Temporal**) for long\-running AI/automation workflows. * Familiarity with **Model Context Protocol (MCP)** for tool integration and extensible agent systems. * Experience with LLM/agent evaluation frameworks (e.g., **BrainTrust**, **DeepEval**, or similar). Target salary range: $120,001 \- $160,000\. The estimate displayed represents the typical salary range for this position based on experience and other factors.