Applied AI Tech Lead - ACG / AEA
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