Core responsibilities:

Lead hands-on implementation of the enterprise search platform in the customer's cloud environment, working alongside IPNS leadership and customer engineering teams Build and tune data ingestion pipelines across diverse sources (SharePoint, network drives, structured databases), including document parsing, chunking strategy, metadata extraction, and sensitivity classification Implement and optimize the embedding and indexing layer: Vertex AI embedding models, Elasticsearch vector search (dense_vector/kNN), and federated multi-index retrieval Own retrieval quality: relevance tuning, hybrid search (semantic plus keyword), evaluation frameworks, and iterative improvement based on user feedback Configure and extend the multi-agent orchestration layer (query decomposition, specialized domain agents, response validation) and integrate with the customer's existing chat interface Ensure the implementation meets federal security and compliance requirements (FedRAMP High alignment, role-based and document-level access controls) Support POC milestones, customer demos, and technical working sessions with agency stakeholders and prime contractor partners Key qualifications/experience: 5+ years in search/information retrieval, ML engineering, or data engineering, with 2+ years building LLM/RAG systems in production (not just prototypes) Significant Elasticsearch (or similar) experience: index design, relevance tuning, vector search; cross-cluster search a strong plus Google Cloud AI stack: Vertex AI (Vector Search, embedding models, Gemini), plus supporting services like Dataflow, Document AI, and GKE Strong Python and data manipulation skills: ETL pipelines, regex, parsing messy structured and unstructured data at scale Practical understanding of embeddings, chunking strategies, hybrid retrieval, and RAG evaluation methods Experience with agent frameworks or multi-agent orchestration a plus US citizenship required; must be able to obtain and maintain a federal background investigation. Active clearance or prior DHS suitability determination a strong plus Prior federal or regulated-environment delivery experience a plus Self-directed and comfortable in a small-company environment where you'll wear multiple hats Why IP Network Solutions (IPNS) At IPNS, you will work on high-impact national security and border protection missions , delivering cutting-edge AI/ML solutions that directly support CBP operators and decision-makers. This role offers the opportunity to shape AI capabilities from inception to operational deployment in a real-world federal mission environment.

Job Type:

Part-time Pay:

From $175,000.00 per year Application Question(s): Do you have experience working with MLOps, containerization (Docker), and orchestration (Kubernetes)?

Security clearance:

Top Secret (Required)

Work Location:

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