Applied AI Tech Lead - ACG / AEA

<p>Description</p><p>Contingent Contract Award</p><p><strong>6 month opportunity</strong></p><p>Remote&nbsp;</p><p>Springfield, VA</p><p><br/></p><p><strong>Connected Logistics</strong> is seeking<strong> Applied AI Tech Lead</strong> to be the &nbsp;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.&nbsp;</p><p><br/></p><p>&nbsp;<strong>Key Responsibilities:</strong></p><ul><li>Architect &nbsp;end-to-end AI/ML solutions, including RAG pipelines, embedding strategies, vector indexing, and inference workflows.</li><li>Define and implement model lifecycle controls: versioning, evaluation, audit logging, traceability, and rollback.</li><li>Design secure integration patterns across AWS, Azure, Salesforce, and Azure DevOps.</li><li>Establish governance aligned to RMF constraints, including PII/CUI handling, prompt control, and usage auditing.</li><li>Define model evaluation frameworks (precision/recall, relevance scoring, latency, SLA adherence).</li><li>Implement monitoring for model performance, drift detection, and data quality degradation.</li><li>Oversee CI/CD integration for model deployment, retraining, and rollback.</li><li>Lead root-cause analysis and triage automation architecture (classification, similarity search, SLA prediction).</li><li>Review and enforce coding standards for ML pipelines, APIs, and data flows.</li><li>Mentor engineers and direct technical execution across data, model, and integration layers.</li></ul><p>Requirements</p><ul><li>Minimum 10 years’ experience in AI/ML engineering, data science, or distributed systems development.</li><li>Master’s degree required (no exceptions) in Computer Science, Engineering, Mathematics, or related field.</li><li>&nbsp;Must have an <strong>Active Public Trust</strong> clearance or higher.</li><li>&nbsp;Must have been issued a CAC by another government client in the last 24 months.</li><li>Deep experience with RAG architectures (embeddings, vector DBs, retrieval optimization).</li><li>Strong Python proficiency and experience building production ML services and APIs.</li><li>Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM integration patterns.</li><li>Hands-on experience with cloud-native architectures (AWS and/or Azure)</li><li>Experience integrating AI components into CI/CD pipelines (build, test, deploy).</li><li>Experience working in regulated or secured environments with audit and compliance requirements.</li></ul><p><strong>Must have Skill Sets (Technical + Methodologies)&nbsp;</strong></p><p><br/></p><p><u>RAG Architecture (hands-on experience)</u></p><ul><li>Embeddings (OpenAI, HF, or similar)</li><li>Vector databases (Pinecone, OpenSearch, FAISS, or equivalent)</li><li>Retrieval tuning (top-k, re-ranking, grounding strategies)</li></ul><p><u>LLM Integration Patterns</u></p><ul><li>Prompt engineering with versioning/control</li><li>Context window optimization</li><li>Guardrails and response validation</li></ul><p><u>Model Lifecycle Management</u></p><ul><li>Model versioning and registry concepts</li><li>Evaluation frameworks (precision/recall, relevance scoring)</li><li>Drift detection and performance monitoring</li></ul><p><u>Cloud-Native Architecture (must be hands-on)</u></p><ul><li>AWS (Lambda, S3, Bedrock/SageMaker) and/or Azure (ML, Functions, Storage)</li><li>Secure service-to-service integration patterns</li><li>API-first design</li></ul><p><u>DevSecOps Integration</u></p><ul><li>CI/CD pipelines (Azure DevOps, Git-based workflows)</li><li>Automated testing for ML systems</li><li>Deployment strategies (blue/green, rollback)</li></ul><p><u>Data + ML Pipeline Integration</u></p><ul><li>End-to-end flow: ingestion to transformation to embedding to retrieval to inference.</li><li>Handling structured + unstructured data in production systems.</li></ul><p><u>Security &amp; Governance Implementation</u></p><ul><li>PII/CUI handling-in pipelines</li><li>Audit logging and traceability design</li><li>Access control patterns for ML systems</li></ul><p><u>System Design for Enterprise Workflows</u></p><ul><li>Event-driven and microservices architecture</li><li>Integration into existing systems (e.g., Salesforce, ticketing systems)</li><li>High - availability / low - latency design</li></ul><p><br/></p><p><u><strong>Total Rewards Statement</strong></u></p><p><br/></p><p>We believe in fairness and clarity throughout our hiring process. The anticipated salary range for this position is <strong>$160,000.00 to $170,000.00 USD</strong>. This is a good-faith range based on factors such as your experience, geographic location, and any applicable contractual requirements, and may vary slightly.</p><p><br/></p><p>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!</p><p><br/></p><p><strong>Connected Logistics</strong> respects the need for confidentiality for all applicants.</p><p><br/></p><p><strong>Connected Logistics</strong> offers an excellent benefits package that includes health, dental, vision, life, and disability insurance, a great 401(k) package, and generous Paid Time Off.</p><p><br/></p><p>&nbsp;<strong>EOE/Disability/Veterans</strong></p>