AI Solution Engineer- Ops

Responsibilities

• Execute ETL pipelines for supply chain data ingestion including customer technical data packages, transformation, and loading into the Exiger environment
• Run and monitor ML model inference jobs, flagging anomalies and performance degradation to the lead
• Build and maintain data pipeline automation using Python, SQL, and orchestration frameworks (Airflow, Spark, dbt, or equivalent)
• Produce analytics outputs that feed Red Team vulnerability assessments and Blue Team mitigation planning
• Participate in data quality validation workflows and contribute to confidence scoring documentation
• Support iterative analytics configuration releases based on Government feedback cycles
• Maintain pipeline documentation, run logs, and provenance records per program governance standards
• Required Qualifications
• Minimum 4 years of experience in data science, analytics engineering, ML operations, or AI
• Proficiency in Python, SQL, and data pipeline tools (Airflow, Spark, pandas, dbt, or equivalent); working knowledge of relational and cloud data platforms (PostgreSQL, Snowflake, or equivalent)
• Experience with ETL/ELT processes, data transformation, and analytics production workflows across structured and semi-structured data sources
• Familiarity with ML model deployment and monitoring in cloud environments (AWS, Azure, or equivalent)
• Experience working under technical oversight in an integrated government delivery team
• Strong documentation practices and ability to maintain auditable process records

Requirements

• Experience with ETL/ELT processes, data transformation, and analytics production workflows across structured and semi-structured data sources
• Familiarity with ML model deployment and monitoring in cloud environments (AWS, Azure, or equivalent)
• Experience working under technical oversight in an integrated government delivery team
• Strong documentation practices and ability to maintain auditable process records
• Experience with supply chain data, entity resolution, or risk analytics
• Familiarity with government data handling requirements (CUI, NIST 800-171)
• Experience with containerized deployments (Docker/Kubernetes)
• Experience with PostgreSQL, Snowflake, or similar cloud data warehouse platforms in production analytics environments
• About PingWind
• www.PingWind.com
• Our benefits include:
• Eleven Federal Holidays
• Paid Time Off accrued each pay period
• Parental Leave
• Three medical plan choices with generous employer contribution
• Dental and Vision Insurance
• Company paid Short-Term and Long-Term Disability
• Company paid Life and AD&D Insurance
• 401k with competitive matching and vesting schedule
• Continuing education assistance
• Short Term / Long Term Disability & Life Insurance
• Medical, Dependent Care and Commuter Flexible Spending Accounts
• Employee Assistance Program
• Wellness benefits include Calm Health app and WellHub gym subsidy (formerly GymPass)
• 529 College Savings Plan
• Legal Insurance
• Pet Insurance
• Veterans are encouraged to apply
• PingWind, Inc. does not discriminate in employment opportunities, terms, and conditions of employment, or practices on the basis of race, age, gender, religious or political beliefs, national origin or heritage, disability, sexual orientation, or any characteristic protected by law

Additional Information

Location: Huntsville, AL or Washington, DC Required Clearance: TS/SCI Eligible Required Education: HS/GED Required Experience: Minimum of 4 years of experience in data science, analytics engineering, ML, operations, or AI Hybrid: 3 days of onsite/ 2 days remote Position Description This position supports the Golden Dome Supply Chain Enterprise program by executing analytics workflows, data ingestion pipelines, and machine learning model operations within the operations and implementation branch. The engineer works under the technical direction of an Exiger AI Solution Engineer lead, executing ETL processes, analytics production runs, and pipeline maintenance that feed the program's Red Team and Blue Team analytic constructs

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