Solution Engineer

Responsibilities

• Develop and deliver technical demonstrations, proof-of-concepts, and whitepapers to showcase Data and AI Practice capabilities, including but not limited to areas such as Machine Learning (ML), Data Management, and Enterprise Data Analytics.
• Support opportunity shaping and qualification efforts through technical research and solutioning activities across Intel and Homeland Security, Defense and Space, and Commercial sectors.
• Maintain a strong understanding of traditional machine learning frameworks, enterprise data governance, government compliance requirements, and integration methods with secure enterprise systems.
• Participate in color team reviews (e.g., pink, red) and lead the refinement of solution content throughout the proposal lifecycle.
• Support internal capability development by contributing reusable data architectures, data science patterns and algorithms, and solution accelerators, and collaborating across MANTECH’s technical community.
• Draft and contribute to technical volumes of RFI and RFP responses, ensuring alignment with customer requirements and mission objectives.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• 10+ years of experience in IT solution development, systems engineering, or pre-sales engineering with a focus on data and ML technologies.
• Foundational Technical Skills: Strong proficiency in Python for data science, data manipulation, and pipeline development.
• Core Concepts: Solid understanding of traditional Machine Learning (ML) methodologies, Data Management, and Data Engineering principles.
• Experience working within the Intelligence Community, DoD, or FedCiv markets.
• Strong working knowledge of Enterprise Data Platforms (e.g., Snowflake, Databricks, IBM Cloud Pak for Data, Oracle Cloud Infrastructure Data Platform).
• Strong working knowledge of Cloud Services (e.g., AWS, Azure, GCP, OCI).
• Experience responding to RFIs/RFPs and working on proposal teams in government contracting environments.

Qualifications

• Background in implementing ML pipelines or data analytics platforms in secure or classified environments.
• Experience with MLOps, containerization (Docker, Kubernetes), and strict data governance.
• Proficiency with ML development platforms and tools, such as AWS SageMaker, Jupyter, Palantir, and Snorkel.
• Experience working as a solution engineer for a major Federal consulting firm, FSI, or enterprise software provider.
• Experience developing staffing plans and work breakdown structures (WBSs) to support solution planning and proposal efforts.