Candidates must present proof of U.S. citizenship before hire.
Candidates must be able to obtain and maintain a U.S. Secret clearance.
A bachelor's degree in Computer Science, Data Science, Engineering, or a related discipline, or equivalent work or military experience, is required.
At least 7 years of progressive experience in solutions architecture, data engineering, AI/ML engineering, or software engineering is required.
At least 2 years leading engineers or technical teams, including planning, prioritization, mentoring, and performance feedback, is required.
Candidates must have a demonstrated record of delivering AI or automation solutions to production in enterprise environments, on schedule and with measurable business results.
Candidates must have hands-on experience with a modern cloud data platform and AWS infrastructure, including infrastructure as code.
Candidates must have experience with data pipelines and integrations using Python, SQL, and REST APIs.
Candidates must have experience managing budgets, vendors, and build-versus-buy decisions.
Candidates must be able to engage non-technical stakeholders, set expectations, and drive cross-functional alignment.
Candidates must have experience operating in regulated environments and familiarity with CMMC, NIST SP 800 series, DFARS, or equivalent requirements.
Candidates must have strong written and verbal communication skills, including executive-level reporting.
Responsibilities
Own the AI and 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 work against business impact, effort, and risk, and sequence work when capacity is limited.
Track and report progress, blockers, and risks weekly, and escalate early.
Define success metrics for every solution, such as hours saved, cycle time, and cost avoided, and verify results after launch.
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.
Meet regularly with business unit leaders to understand pain points and quantify opportunities.
Challenge requests to automate existing processes when redesigning the 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.
Define the target architecture for the AI and Automation platform, using Snowflake as the data platform, AWS as supporting cloud infrastructure, and Terraform to manage infrastructure as code.
Set technical standards, integration patterns, and data pipeline designs that make delivery repeatable.
Review team designs, resolve technical trade-offs, and remain hands-on with prototyping and debugging production issues as needed.
Ensure solutions are observable, supportable, and documented with runbooks before handoff.
Assess commercial platforms versus custom builds based on cost, speed, security, scalability, and maintainability.
Develop business cases and recommendations for executive review.
Run vendor evaluations, proofs of concept, and contract negotiations with finance, legal, and cyber teams, and manage vendor performance and spend after purchase.
Manage the AI program budget, including tooling, cloud consumption, and headcount, and keep spending 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.
Design every solution using 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.
Desired Qualifications
At least 10 years of experience 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 such as Claude, and workflow automation platforms such as n8n.
Experience with retrieval-augmented generation pipelines, embeddings, and vector databases.
Experience evaluating and implementing commercial AI and automation platforms at enterprise scale.
Experience with Agile delivery, continuous integration and continuous delivery, and DevSecOps practices.
Advanced certifications in cloud architecture, AI/ML, data engineering, or project/program management.
Snowflake experience is preferred.
Terraform experience is preferred.
Overview
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.
Key Responsibilities
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.
Qualifications
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
Preferred Qualifications
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
$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
Industrial Security Integrators, LLC ("IsI") is an equal opportunity employer committed to affirmative action and diversity in the workplace. It is the policy of IsI to provide Equal Employment Opportunities (EEO) to Employees and Applicants, without regard to race, color, religion, sex, age, marital status, citizenship status, national origin, sexual orientation, gender identity, veteran status or disability or any other factor protected by law and to provide advancement opportunities for minorities, women, disabled individuals, and veterans. IsI is stronger and more effective when our workforce includes highly qualified individuals with diverse backgrounds, cultures, and traditions.
IsI Enterprises does not accept unsolicited resumes from individual recruiters or third party recruiting agencies in response to job postings or otherwise. Placement fees will not be paid to any recruiter unless IsI has an active agreement in place with the recruiter and such a request has been made by the IsI hiring team and such candidate was submitted to the IsI hiring team via our Applicant Tracking System. Any unsolicited resumes or other data submitted to IsI in violation of this policy may be used by IsI without obligation to pay any fees of any kind to the recruiter.