Applied AI Tech Lead - ACG / AEA
Fully Remote Springfield, VA
Description

Contingent Contract Award

6 month opportunity

Remote 

Springfield, VA


Connected Logistics is seeking Applied AI Tech Lead to be the  technical authority over AI/ML architecture, integration, and governance within a controlled DevSecOps environment. The AI Tech Lead will own design and implementation of retrieval-augmented generation(RAG), model lifecycle management, and secure integration of AI capabilities into enterprise workflows and pipelines. 


 Key Responsibilities:

  • Architect  end-to-end AI/ML solutions, including RAG pipelines, embedding strategies, vector indexing, and inference workflows.
  • Define and implement model lifecycle controls: versioning, evaluation, audit logging, traceability, and rollback.
  • Design secure integration patterns across AWS, Azure, Salesforce, and Azure DevOps.
  • Establish governance aligned to RMF constraints, including PII/CUI handling, prompt control, and usage auditing.
  • Define model evaluation frameworks (precision/recall, relevance scoring, latency, SLA adherence).
  • Implement monitoring for model performance, drift detection, and data quality degradation.
  • Oversee CI/CD integration for model deployment, retraining, and rollback.
  • Lead root-cause analysis and triage automation architecture (classification, similarity search, SLA prediction).
  • Review and enforce coding standards for ML pipelines, APIs, and data flows.
  • Mentor engineers and direct technical execution across data, model, and integration layers.
Requirements
  • Minimum 10 years’ experience in AI/ML engineering, data science, or distributed systems development.
  • Master’s degree required (no exceptions) in Computer Science, Engineering, Mathematics, or related field.
  •  Must have an Active Public Trust clearance or higher.
  •  Must have been issued a CAC by another government client in the last 24 months.
  • Deep experience with RAG architectures (embeddings, vector DBs, retrieval optimization).
  • Strong Python proficiency and experience building production ML services and APIs.
  • Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM integration patterns.
  • Hands-on experience with cloud-native architectures (AWS and/or Azure)
  • Experience integrating AI components into CI/CD pipelines (build, test, deploy).
  • Experience working in regulated or secured environments with audit and compliance requirements.

Must have Skill Sets (Technical + Methodologies) 


RAG Architecture (hands-on experience)

  • Embeddings (OpenAI, HF, or similar)
  • Vector databases (Pinecone, OpenSearch, FAISS, or equivalent)
  • Retrieval tuning (top-k, re-ranking, grounding strategies)

LLM Integration Patterns

  • Prompt engineering with versioning/control
  • Context window optimization
  • Guardrails and response validation

Model Lifecycle Management

  • Model versioning and registry concepts
  • Evaluation frameworks (precision/recall, relevance scoring)
  • Drift detection and performance monitoring

Cloud-Native Architecture (must be hands-on)

  • AWS (Lambda, S3, Bedrock/SageMaker) and/or Azure (ML, Functions, Storage)
  • Secure service-to-service integration patterns
  • API-first design

DevSecOps Integration

  • CI/CD pipelines (Azure DevOps, Git-based workflows)
  • Automated testing for ML systems
  • Deployment strategies (blue/green, rollback)

Data + ML Pipeline Integration

  • End-to-end flow: ingestion to transformation to embedding to retrieval to inference.
  • Handling structured + unstructured data in production systems.

Security & Governance Implementation

  • PII/CUI handling-in pipelines
  • Audit logging and traceability design
  • Access control patterns for ML systems

System Design for Enterprise Workflows

  • Event-driven and microservices architecture
  • Integration into existing systems (e.g., Salesforce, ticketing systems)
  • High - availability / low - latency design


Total Rewards Statement


We believe in fairness and clarity throughout our hiring process. The anticipated salary range for this position is $160,000.00 to $170,000.00 USD. This is a good-faith range based on factors such as your experience, geographic location, and any applicable contractual requirements, and may vary slightly.


Beyond salary, we provide a robust benefits package and encourage ongoing professional development, because your growth and well-being matter to us. We’re excited to support you in building a rewarding career with us!


Connected Logistics respects the need for confidentiality for all applicants.


Connected Logistics offers an excellent benefits package that includes health, dental, vision, life, and disability insurance, a great 401(k) package, and generous Paid Time Off.


 EOE/Disability/Veterans