AI/Data Solutions Engineer TS/SCI (FSP)

Introduction At IBM, the work is about building things that matter. You will be working on real problems in a mission environment where the output of your work is used, not just presented. We are looking for a hands-on data and engineering professional who can take messy, incomplete information and turn it into something useful and clear. This role is about going from raw data to real understanding and doing it in a way that people can act on immediately, with confidence. You will work across the full lifecycle of work. That includes getting data, shaping it, building models where needed, and delivering outputs that help people make decisions. This is not a role where someone hands you a clean dataset or defined problem. You will also work closely with junior team members. Part of your responsibility is helping them grow into strong, independent contributors by working alongside them, giving them ownership, and holding a high bar for quality. Your Role And Responsibilities Candidate is required to have US Citizenship for this role without exception. Candidates must also have an approved, active US Government Top Secret/SCI security clearance with Full Scope Polygraph and be able to sit onsite in the Washington DC Metro area. The Data Solutions Engineer is a hands-on technologist and problem solver who works across data, systems, and analysis to deliver outcomes that are usable in real mission conditions. This role is responsible for contributing to solutions that take raw, fragmented data and turn it into something clear, reliable, and actionable. The focus is on building work that holds up in operational use, not just in controlled environments. You will contribute across the workflow, from how data is handled through how it is used, making practical decisions that balance technical quality with mission needs. You Will • Work directly with raw and incomplete data, determining how to structure, process, and use it effectively. • Develop and apply models and analytical methods to identify meaningful patterns, behaviors, and signals. • Build and support data pipelines that enable consistent, repeatable processing across datasets. • Integrate internal and external models into working systems and adjust them as conditions or data changes. • Operate effectively in secure and constrained environments where tradeoffs are required. Team Development And Collaboration • Work directly with junior data engineers and data scientists as part of day-to-day delivery. • Help them take ownership of defined components and hold them accountable for outcomes. • Provide direct feedback through code review and working sessions. • Break down complex problems so others can contribute and build confidence. • Support a team environment where responsibility is shared and expectations are clear. Preferred Education Bachelor's Degree Required Technical And Professional Expertise Clearance & Logistics: US Citizenship is required. Candidates must possess an active Top Secret/SCI (TS/SCI) clearance with a Full Scope Polygraph on Day 1 and be able to work onsite in the Washington, DC Metro Area (Chantilly, VA). Work is performed in a secure environment with limited remote flexibility. Education & Experience: Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field, or equivalent practical experience, with 5 or more years of experience in data science, machine learning, or applied data roles, with a track record of applying skills to real-world problems. Programming & Data Fundamentals: Strong proficiency in Python and working knowledge of SQL. Demonstrated ability to work directly with raw data to explore, transform, and analyze datasets without relying on pre-built tooling. Data Processing & Systems: Experience contributing to data pipelines and processing workflows, including ingestion and transformation, and handling of large or complex datasets. Applied Modeling and Analysis: Experience building and applying models or analytical approaches in real-world settings, with an understanding of how to adapt to changing data and requirements. Data Types & Complexity: Experience working with multiple forms of data such as text, imagery, video, or sensor data, and the ability to extract meaningful patterns from incomplete or noisy inputs. Operational & Secure Environment: Experience working in distributed, standalone, or secure environments, adapting approaches to system and security constraints. Model Use & Lifecycle Awareness: Experience putting models or analytical outputs into use and monitoring performance over time, including recognizing when adjustments are needed. Ways of Working: Ability to operate effectively in team-based environments with shared ownership and accountability. Demonstrates sound judgement when working through ambiguous or evolving problems and contributes to both delivery and team capability. Preferred Technical And Professional Experience Candidates may come from different technical backgrounds but should demonstrate exposure across data, systems, and analysis. Mission & Domain Experience: experience supporting or delivering solutions within the IC or DoD, particularly in secure, mission-driven, or air-gapped environments. Data & Analytical Techniques: experience working with imagery data or applying computer vision techniques. Familiarity with newer modeling approaches when applied in practical, real-word settings. Data Processing & Systems: experience working with real-time or streaming data or building workflows that support continuous data processing and analysis. Strong preference for candidates who default to code-driven analysis rather than relying on GUI-based tools. Cloud & Infrastructure Exposure: exposure to clou or hybrid environments within secure constraints, with an understanding of how infrastructure impacts data and system design. Integration & Tooling: experience with APIs, system integration, or container-based workflows, including adapting tools and components to fit within larger systems. Team Development & Growth: demonstrated ability to support and develop junior team members through hands-on collaboration, guidance, and shared delivery of work.