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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI/ML & Data Engineer - **Company:** Accenture - **Location:** Chantilly, VA, United States - **Experience:** Expert - **Salary:** $100,200.0 - $203,400.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automated Storage and Retrieval Systems, Microsoft Azure, BigQuery, Cloud Computing, Cloud Engineering, Cyber Security, Continuous Integration, Data Validation, Information Engineering, Extract Transform Load (ETL), Graph Database, Python (Programming Language), Machine Learning, Tensorflow, Zero Trust Network Access, Azure Machine Learning, Search Technologies, Data Logging, Pytorch, System Availability, Large Language Models, Snowflake, Model Validation, Generative AI, Gitlab, Cloudformation, Containerization, Data Lakes, Scikit Learn, Kubernetes, Infrastructure Automation Frameworks, Information Technology, HuggingFace, Machine Learning Operations, Terraform, Stream Processing, Software Version Control, Data Pipelines, Devsecops, Docker, Jenkins, Databricks, Microservices - **Published:** July 28, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9060843/senior-aiml-data-engineer ## About the Role * Bachelor's or Master's degree in Computer Science, Engineering, Applied Mathematics, or related field. * 5+ years of experience in one or more of the following areas: + AI/ML engineering, cloud-native development, or data engineering. + Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit-learn). + Hands on experience with LLM development (OpenAI, Anthropic, Bedrock, Azure OpenAI, HuggingFace Transformers). + Experience architecting ML pipelines using AWS, Azure, or GCP. + Familiarity with DevSecOps and IaC tools (Terraform, CloudFormation, Jenkins, GitLab, etc.). + Experience implementing microservices, APIs, and containerized workloads (Docker, Kubernetes, ECS/EKS/AKS). Bonus points if you have: * Experience building RAG pipelines with vector databases (Pinecone, FAISS, Weaviate, Milvus). * Experience designing agentic workflows and multi agent AI systems. * Experience with graph databases, knowledge graphs, or semantic search. * Certifications such as AWS Architect, AWS ML Specialty, Azure AI Engineer, Security+. * Ability to translate complex technical concepts for non-technical audiences. * Strong problem-solving abilities with a product focused mindset. * Strong communication and client facing consulting skills. * Ability to work across cross-functional teams in a fast-paced environment. * Understanding of security frameworks (FedRAMP, NIST 800 53, Zero Trust) for ML systems. Security clearance: * Active Top Secret (TS) security clearance is required; and must be able and willing to upgrade to TS/SCI with Poly. ## Description We are looking for an experienced Senior AI/ML and Data Engineer to develop, implement, and maintain sophisticated machine learning, LLM, and enterprise AI solutions for our federal client. The ideal candidate combines strong hands on engineering talent with architectural leadership-capable of shaping mission aligned AI strategy, designing scalable pipelines, and delivering production-grade ML and Generative AI capabilities in secure environments. This role will partner with cross functional teams - including data engineering, cloud engineering, cybersecurity, and mission SMEs - to architect end-to-end AI systems that are reliable, compliant, and impactful. The work you'll do: * AI/ML Engineering: + Design, develop, and deploy machine learning models, LLM applications, retrieval augmented generation (RAG) pipelines, and agentic AI systems. + Build data preprocessing, training, fine tuning, inference, and evaluation workflows. + Develop scalable ML pipelines using modern toolchains (SageMaker, Bedrock, Azure ML, Databricks, Ray, HuggingFace). + Implement MLOps solutions including CI/CD for ML, model versioning, monitoring, logging, and drift detection. + Shape AI system design decisions including vector DB selection, embedding strategies, prompt architecture, and model selection. + Define target state architectures for LLM enabled applications, AI microservices, RAG pipelines, and knowledge retrieval systems. * Data & Cloud Engineering: + Design, build, and maintain scalable automated data pipelines (ETL/ELT) to support both batch and real-time data processing. + Architect data lakes and warehouses (e.g., Snowflake, Databricks, BigQuery) to ensure high availability and performance for ML workflows. + Implement rigorous data quality checks and validation frameworks to ensure "garbage-in, garbage-out" never applies to our models. * Delivery & Stakeholder Engagement: + Work closely with program leadership, technical SMEs, and mission stakeholders to define requirements and AI roadmaps. + Translate business problems into technical AI solutions and communicate tradeoffs to mixed audiences. + Produce architecture diagrams, interface specifications, deployment patterns, and integration plans. ## Related Videos - [WeAreDevelopers LIVE - Modern DevOps for IoT Devices and More](https://www.wearedevelopers.com/videos/1805-wearedevelopers-live-modern-devops-for-iot-devices-and-more) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Our GitOps approach for deploying an Identity Provider and an API Gateway in a SaaS company](https://www.wearedevelopers.com/videos/776-our-gitops-approach-for-deploying-an-identity-provider-and-an-api-gateway-in-a-saas-company) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? 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