Location: Remote
Clearance: Active DoD Secret clearance required
Employment Type: Full-Time (W-2)
Citizenship: U.S. Citizenship required
Intelli Tech is seeking a Senior Data / AI Engineer to support a Department of War program focused on operationalizing a Government-owned digital twin application for ammunition industrial base readiness. The platform is a supply chain simulation solution built on Python, FastAPI, and React that enables analysts to model production timelines, identify bottlenecks, assess supply chain risk, and evaluate surge and modernization scenarios.
This role will own the data lifecycle end-to-end—from raw file ingestion through validation, normalization, versioning, and delivery of run-ready artifacts to the simulation engine. The engineer will also help design and implement the AI-enabled decision-support layer
, supporting natural-language analysis of scenario outputs, automated comparison and briefing generation, and guided scenario creation.
This is a hands‑on role on a lean, senior team. The ideal candidate is comfortable writing production code daily, designing scalable data pipelines, and working directly with Government analysts and data stakeholders to deliver mission-focused solutions.
Key Responsibilities Data Ingestion and Automation- Design and implement governed ingestion pipelines for complex defense supply chain datasets, including Bills of Materials (BOM), demand and order backlogs, facility and production line capacity, supplier risk, and acquisition planning data.
- Build validation services that enforce schema conformance, referential integrity across linked datasets, circular reference detection, and business-rule validation with actionable row‑ and column‑level feedback.
- Implement raw data preservation in object storage such as Amazon S3
, including metadata capture for source type, upload timestamp, uploader identity, file checksum, and dataset version. - Develop canonical data transformation workflows that convert validated source inputs into normalized, run‑ready artifacts aligned to the simulation engine’s entity model.
- Implement dataset versioning and lineage tracking so each scenario run is tied to explicit input versions and assumptions.
- Work with Government stakeholders and source‑system owners to identify, prioritize, and implement automated or semi‑automated data refresh paths.
- Participate in Technical Exchange Meetings (TEMs) to help define data contracts, including source format, semantics, refresh cadence, and validation requirements.
- Implement approved connection patterns such as scheduled file landing, secure file exchange (SFTP), API‑based retrieval, and cloud‑to‑cloud transfer mechanisms.
- Maintain hardened controlled upload workflows in parallel so mission operations are not dependent solely on external integrations or approvals.
- Build the AI integration layer within the FastAPI backend to broker access to Government‑approved hosted LLM endpoints.
- Implement scoped retrieval logic that constrains AI context to approved run artifacts, simulation outputs, and post‑processed analytics.
- Develop natural‑language Q&A capabilities that allow analysts to query scenario results such as bottlenecks, supplier risks, and differences between runs.
- Build guided scenario generation workflows that translate analyst intent into structured JSON scenario configurations for user review and approval before execution.
- Implement AI‑assisted comparison summaries and brief‑ready output generation.
- Enable function calling and tool‑use patterns so the model can dynamically query backend APIs for scenario comparison, bottleneck analysis, production planning, and supply chain risk.
- Ensure all AI interactions are audit‑logged, role‑scoped, and grounded in explicit scenario artifacts.
- Extend existing comparison capabilities to generate structured side‑by‑side scenario outputs with standardized metrics and deltas.
- Build reusable templates for brief‑ready outputs that reduce analyst time‑to‑brief.
- Generate reproducible comparison artifacts and store them as part of the scenario run record.
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