Senior Manager, Growth[x] Data & AI Engineer

Responsibilities

We are hiring a Senior Manager, Growth[x] Data & AI Engineering to serve as the senior technical lead for the data and AI foundation that powers Growth[x], an AI-enabled, end-to-end solution that transforms how we identify opportunities, execute our end-to-end growth pipeline, and deliver winning proposals.

Growth[x] is built on the Peraton[x] platform and unifies the playbooks, data sources, and tooling the Growth organization today into a single, intelligent workflow — from opportunity capture through proposal submission.

Key Responsibilities:

This role is responsible for planning, coordinating, and managing the data pipelines, cortexes, integrations, and governance that make Growth[x] trustworthy, secure, and useful at enterprise scale. You will be the connective tissue between the Growth organization, the CIO's data platform, and the Peraton[x] platform team — ensuring that the right data is available, governed, trusted, and accessible for the right AI-driven purposes.

 

This is a hands-on leadership role. You will architect and build alongside the team, not just direct it.

 

Solution Architecture. Architect the end-to-end technical vision for Growth[x] — how opportunity identification, qualification, capture, color teams, pricing inputs, past performance, solutioning, and proposal development connect into a single AI-enabled workflow on Peraton[x].

 

Cortex Development. Design and stand up the knowledge cortexes (ontology, mission briefing, curated content, KG structure) that power Growth[x]. Establish standards for how cortexes are built, versioned, and maintained as source material evolves.

 

Data Connections & Quality. Lead integration with the CIO managed and governed systems of record Growth depends on and the Peraton Data Warehouse and with cross-corporate functionally owned SharePoint repositories. Drive the data-quality remediation needed to make AI outputs trustworthy.

 

Process Design. Translate end-to-end growth process steps into event triggered data packages for the team, intuitive dashboards, and skills and workflows on Peraton[x]. Partner with Growth process owners to redesign workflows around AI rather than bolting AI onto legacy steps. Partner with the Peraton[x] team to ensure Growth operations remain optimized and evolve as the platform evolves.

 

Playbook Productization. Take the existing library of BAP prompts and playbooks and elevate them into hardened, reusable skills and flows with clear inputs, outputs, and quality gates.

 

Enablement & Training. Build the training curriculum and enablement collateral (tool-specific and process-specific) that gets capture managers, proposal managers, solution architects, and pricing leads productive on Growth[x].

 

Team Leadership. Lead and manage a small, high-leverage team setting technical direction, prioritizing the roadmap, and coaching them into stronger operators.

 

Stakeholder Management. Serve as the senior point of accountability to Growth leadership, IT, security, and the Peraton[x] platform team. Communicate progress, risks, and trade-offs in business terms.

Qualifications Required Qualifications:

• 12+ years of progressive experience in data/AI, solution architecture, or digital transformation, with 5+ years leading technical teams.
• Must have demonstrated ownership of an enterprise AI or analytics platform from architecture through adoption — not just pilots.
• Possess a strong working knowledge of agentic AI systems: prompt engineering, retrieval / knowledge graphs, evaluation, and productionization patterns.
• Experience navigating shared infrastructure models — consuming centrally managed data platforms without owning the underlying infrastructure.
• Prior experience working with or alongside a CIO office or enterprise IT governance function in a consumer/integrator capacity.
• SQL & Databases: Strong command of SQL and experience with relational databases (e.g., PostgreSQL, Microsoft SQL Server).
• ETL / ELT Pipelines: Hands-on experience designing and implementing data pipelines using tools such as Apache Airflow, Informatica, Talend, dbt, or equivalent.
• Cloud Platforms: Experience with AWS and/or Microsoft Azure, including managed data services (e.g., Azure Synapse, ADLS, ADF, BigQuery).
• BI & Visualization: Proficiency with Power BI, Alteryx, or equivalent BI tools.
• Data Warehousing: Familiarity with data warehousing concepts, dimensional modeling, and data lake / lakehouse architecture.
• AI / LLM Foundations: Working knowledge of LLM-based systems — retrieval-augmented generation, knowledge graphs / ontologies, prompt engineering, and evaluation — sufficient to design the data and cortex layer beneath them.
• Excellent written and verbal communication; able to move between executive stakeholders, CIO-office counterparts, and hands-on engineers.
• US. citizenship
• Willing to obtain and maintain a TS/SCI security clearance

Desired Qualifications:

• Working knowledge of the federal Business Acquisition Process, Shipley-style capture and proposal processes, color teams, and proposal artifacts.
• Knowledge of the NIST AI Risk Management Framework (AI RMF) and its data-related implications.
• Relevant certifications: Microsoft Certified: Azure Data Engineer Associate, dbt Certified Developer, CDMP (Certified Data Management Professional), or equivalent.
• Active TS/SCI security clearance.

Target Salary Range$176,000 - $282,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.