AI Engineering Manager

United Statesmid

EngineeringEngineering Manager

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Quick Summary

Overview

OverviewThe AI Engineering Manager is the technical and delivery leader for IsI’s AI & Automation program. You will partner with the Security Control, Managed Services,

Technical Tools

EngineeringEngineering Manager

The AI Engineering Manager is the technical and delivery leader for IsI’s AI & Automation program. You will partner with the Security Control, Managed Services, and Managed Security Services business units to turn their biggest operational bottlenecks into production solutions that deliver measurable efficiency gains and EBITDA impact. This is a player-coach role: you will set architecture direction, lead a small team of engineers, own the delivery roadmap, and stay hands-on enough to unblock the team and make sound build vs. buy calls.
Success in this role is measured by what ships and what it saves: solutions in production, adopted by the business, secure by design, and built on shared platforms (Snowflake, AWS, and workflow automation tooling) rather than one-off implementations.

Responsibilities

~3 min read

Delivery and Execution
Own the AI & Automation roadmap end to end, converting strategy into quarterly milestones, sprint-level plans, and dated commitments. Drive projects from intake through design, build, security review, production release, and adoption, holding the team and stakeholders to clear owners and deadlines. Prioritize ruthlessly against business impact, effort, and risk, and say no or sequence work when capacity is limited. Track and report progress, blockers, and risks weekly, and escalate early. Define success metrics for every solution (hours saved, cycle time, cost avoided) and verify results after launch.
Team Leadership and Management
Lead, mentor, and develop the AI engineering team, including the Data Engineer and AI Software Engineers. Set expectations, run sprint planning and retrospectives, review designs and code, and give regular, direct feedback. Manage capacity and allocation across projects, support hiring and onboarding, and build a culture of ownership, documentation, and secure engineering. Coordinate with engineers and champions embedded from business units so work stays aligned and unblocked.
Business Unit Partnership and Solutioning
Meet regularly with business unit leaders to understand pain points and quantify opportunities. Challenge “automate the current process” requests when a redesigned process would deliver more, and translate business problems into solution designs with clear scope, owners, and outcomes. Set stakeholder expectations, manage dependencies across teams, and ensure solutions serve multiple business units rather than duplicating effort.
Architecture and Platform Design
Define the target architecture for the AI & Automation platform, built on Snowflake as the data platform and AWS as the supporting cloud infrastructure, with infrastructure managed as code in Terraform. Set technical standards, integration patterns, and data pipeline designs that make delivery repeatable. Review team designs, resolve technical trade-offs, and remain hands-on where needed, from prototyping to debugging production issues. Ensure solutions are observable, supportable, and documented with runbooks before handoff.
Build vs. Buy and Vendor Management
Lead objective assessments of commercial platforms versus custom builds, weighing cost, speed, security, scalability, and maintainability. Develop business cases and recommendations for executive review. Run vendor evaluations, proofs of concept, and contract negotiations in partnership with finance, legal, and cyber, and manage vendor performance and spend after purchase.
Budget, Planning, and Reporting
Manage the AI program budget, including tooling, cloud consumption, and headcount, and keep spend within plan. Provide regular updates to executive leadership on delivery status, business impact, and financial results. Maintain a clear record of decisions, designs, and standards for transparency and audit readiness.
Security and Compliance Integration
Design every solution with security-first principles, including least-privilege access, secure data handling, and threat modeling. Evaluate the security posture of third-party AI platforms before adoption. Partner with cloud security and compliance teams to meet CMMC, NIST SP 800 series, DFARS, ITAR, and other applicable requirements, and define guardrails for AI model use, data ingestion, and API integrations. Support internal and external assessments with architecture documentation and evidence of control implementation.

Requirements

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As part of your work at ISI, you will potentially have access to sensitive information from the federal government. Pursuant to applicable regulations, ISI requires that all candidates for this role present proof of U.S. citizenship before hire.
Ability to obtain and maintain a U.S. Secret clearance
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related discipline, or equivalent work or military experience
7+ years of progressive experience in solutions architecture, data engineering, AI/ML engineering, or software engineering
2+ years leading engineers or technical teams, including planning, prioritization, mentoring, and performance feedback
Demonstrated record of delivering AI or automation solutions to production in enterprise environments, on schedule and with measurable business results
Hands-on experience with a modern cloud data platform (Snowflake preferred) and AWS infrastructure, including infrastructure as code (Terraform preferred)
Experience with data pipelines and integrations using Python, SQL, and REST APIs
Experience managing budgets, vendors, and build vs. buy decisions
Proven ability to engage non-technical stakeholders, set expectations, and drive cross-functional alignment
Experience operating in regulated environments with familiarity with CMMC, NIST SP 800 series, DFARS, or equivalent
Strong written and verbal communication, including executive-level reporting

10+ years across solutions architecture, data engineering, and AI/ML
Experience in government contracting or the defense sector
Hands-on experience with large language models, AI coding and automation tools (e.g., Claude), and workflow automation platforms (e.g., n8n)
Experience with RAG pipelines, embeddings, and vector databases
Experience evaluating and implementing commercial AI/automation platforms at enterprise scale
Experience with Agile delivery, CI/CD, and DevSecOps practices
Advanced certifications in cloud architecture, AI/ML, data engineering, or project/program management

What We Offer

~2 min read

✓$150,000–$190,000 annual salary range, commensurate with experience and qualifications

✓Remote work

✓A casual, friendly, and relaxed work environment

✓Professional growth encouragement and support

✓Medical, Dental, and Vision insurance with FSA and HSA options

✓PTO, 11 Paid Holidays, Paid Parental & Military Leave, and more

✓Life & Disability Insurance

✓401K with match

Location & Eligibility

Where is the job

United States

On-site within the country

Who can apply

About this job

Pay per year: $150,000–$190,000 a year; 21% below the $216,300 median for Engineering Manager jobs on Jobera (1,203 salaries).
Who can apply: United States
Posted: 2 days ago
Employer: has 14 open jobs on Jobera.