1 day ago
Remote, United StatesSenior
Responsibilities
- Modernize GMF and related legacy workloads by refactoring monoliths and batch processes into secure cloud-native architectures with embedded AI and automation.
- Design, build, and deploy LLM- and agentic AI-based solutions using LangChain, LangGraph, RAG, vector search, and AWS Bedrock agents.
- Implement platform engineering and MLOps/AIOps practices, including infrastructure as code, CI/CD, model and prompt lifecycle management, and responsible AI controls.
- Collaborate with architects, developers, testers, and stakeholders on 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 a related field.
- At least 9 years of experience in software, ML, or data engineering, including application modernization.
- At least 4 years of experience building and deploying AI/ML or LLM-based applications in production.
- Hands-on experience building agentic AI solutions with LLM frameworks such as LangChain and LangGraph.
- Proficiency in Python and common ML/NLP libraries such as Hugging Face, Transformers, scikit-learn, and PyTorch or TensorFlow.
- Production experience with AWS services including networking/IAM, Lambda, ECS/EKS, API Gateway, S3, DynamoDB, RDS, OpenSearch, SageMaker, and CloudWatch.
- Practical AWS Bedrock experience for LLM-powered applications and agents, including knowledge bases and guardrails.
- Experience with RAG, vector search or databases, SQL, Docker, Kubernetes, AWS ECS/EKS, CI/CD, and infrastructure as code using Terraform or CloudFormation.
- Familiarity with MLOps/AIOps, MLflow, AI observability, logging, metrics, drift monitoring, and quality monitoring for LLM and agent workflows.
- Ability to obtain and maintain a public trust requiring U.S. Citizenship or Green Card.
- Strong technical judgment and communication skills, with the ability to explain AI modernization approaches to technical and business stakeholders.
- Experience with Databricks, Delta Lake, ML or feature stores, LangSmith, CrewAI, AutoGen, Temporal, Model Context Protocol, BrainTrust, or DeepEval is desired.
- Experience operating agents in production, including safety and guardrails, performance tuning, lifecycle management, and multi-agent workflows is desired.
- Experience with payment systems, trading systems, or other highly secure transactional environments is a strong plus.
Tech Stack
Categories
About SAIC
SAIC (Science Applications International Corporation) is a government technology integrator delivering systems engineering, enterprise IT, secure cloud, cybersecurity, C5ISR, and data analytics for U.S. defense, space, intelligence, and civilian agencies. It builds and sustains mission IT and digital engineering solutions under multi-year federal contracts and task orders. Founded in 1969, SAIC is headquartered in Reston, Virginia, and is a public company traded on the NYSE under the ticker SAIC.