Senior AIML & Data Engineer

Job 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 leadershipcapable 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 youll 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.

Heres what youll need:

• Bachelors or Masters 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.