Sr. Manager AI & Software Engineering

Mini-Circuits•Melville, NY

About The Position

Mini-Circuits designs, manufactures and distributes integrated circuits, modules, and sub-systems for high performance radio frequency (RF) and microwave applications. With design, sales and manufacturing locations in over 30 countries, Mini-Circuits’ products are used in a range of wired and wireless communications applications. Our products are also used in detection, measurement and imaging applications, including military communication, guidance and electronic countermeasure systems, commercial, scientific, military land, sea and aircraft; automotive systems, medical systems, and industrial test equipment. Mini-Circuits’ sells its products to over 20,000 customers globally through our direct sales force, applications engineering staff, sales representatives, as well as through our extensive web site. The Sr. Manager AI & Software Engineering will lead the engineering delivery function for Mini-Circuits’ AI, software engineering, digital application, and AI-enabled platform initiatives. This role is responsible for transforming AI and software efforts from project-by-project execution into a disciplined, scalable, production-ready engineering capability. The role will manage delivery across MC-CORE, Ask MC, PIM AI, Project Everest AI enablement, Project Atlas analytics/AI enablement, internal software development, application integrations, and future AI product pods. This position partners closely with IT Operations, Business Applications, Cybersecurity, Enterprise Data Architecture, PMO, business stakeholders, external vendors, and internal software/AI engineering resources. The role is expected to establish delivery cadence, backlog discipline, engineering standards, release readiness, documentation expectations, and production handoff discipline while ensuring that AI and software solutions remain aligned to Mini-Circuits’ business priorities, security requirements, data readiness standards, and customer-focused operating model.

Requirements

Bachelor’s Degree in Software Engineering, Computer Science, or related field of study required.
7-10 years of progressive experience within enterprise business application design and systems development, including system integrations with ERP systems, preferably with SAP.
5+ years of project management responsibility, demonstrating leadership skills, and possessing a track record of managing technical staff.
5+ years of leading large-scale, company-wide systems initiatives to successful execution.
Possess a digital and innovative mindset / knowledge base / and experience that goes beyond simply awareness or managing; must have a deep technical understanding and track record of success in a modernization journey.
Understands the company's business goals and objectives, the business process, and impact of individual actions on business performance.
Applies cost-effectiveness, competitiveness and profitability to business decisions and initiatives.
Proven success working with multiple legacy and custom-built applications while leading company-wide transformation initiatives that result in reduced redundancy, synergy across systems and enterprise applications, and accessible/centralized data.
Demonstrated ability building strong collegial relationships; builds trust through active listening and encouraging a collaborative and open exchange of ideas; reads situations and dynamics accurately and works to bring harmony and productive outcomes.
Gains buy-in and commitment from leadership and staff.
Demonstrates excellent negotiating skills and is able to balance conflicting interests and find win-win solutions to seemingly impossible solutions.
Experience implementing AI initiatives as part of a comprehensive IT strategy
Experience working in large, complex, dynamic organizations with multiple business groups and broad geographic reach and the ability and tolerance to work in an ambiguous environment.
Exceptional communication skills with the ability to leverage internal and external networks in a fast pace, growing organization
Ability and willingness to abide by Company’s Code of Conduct

Nice To Haves

Master’s Degree preferred
Experience in the hi-tech manufacturing industry preferred.

Responsibilities

Lead AI and software engineering delivery across MC-CORE, Ask MC, PIM AI, Project Everest AI enablement, Project Atlas AI/analytics support, internal digital applications, integrations, workflow automation, and future AI product pods.
Own the AI/software engineering delivery operating system, including backlog structure, prioritization discipline, sprint or delivery cadence, release planning, dependency management, blocker escalation, and delivery scorecards.
Translate AI and digital strategy into executable engineering roadmaps, product backlogs, release plans, technical milestones, and measurable business outcomes.
Coordinate AI platform resources, AI product development resources, global software developers, consultants, and vendor engineering contributors into a common engineering cadence with clear ownership and deliverables.
Partner with the VP, AI & Digital Technologies to ensure engineering priorities align with business strategy, operating model maturity, governance requirements, and investment decisions.
Partner with IT Operations to ensure production readiness, environment readiness, support handoff, identity/access alignment, operational documentation, incident process, and service transition before AI/software release.
Partner with Enterprise Data Architecture to ensure AI and software solutions consume approved data sources, documented lineage, defined data quality rules, semantic definitions, and AI-ready datasets.
Partner with Cybersecurity and Architecture/TDA stakeholders to ensure solutions meet architecture standards, security controls, access rules, data classification requirements, and production-risk expectations.
Establish and maintain engineering standards, including coding practices, documentation expectations, code review discipline, testing expectations, DevOps/release controls, technical decision logs, issue escalation pathways, and exception management.
Ensure MC-CORE evolves as a reusable enterprise AI platform, supporting secure retrieval patterns, APIs, evaluation frameworks, model gateway patterns, logging, monitoring, and reusable integration approaches.
Ensure Ask MC and other AI products are developed with named business owners, SME validators, approved data sources, release plans, adoption metrics, and support models.
Coordinate global AI/software engineering capacity, including internal and distributed developers, so work is assigned by product/pod priorities rather than informal task routing.
Maintain visibility into resource capacity, skill gaps, vendor dependency, technical debt, delivery risks, support implications, and future staffing needs.
Partner with PMO / Vendor Governance to manage delivery health, RAID items, vendor scorecards, SOW acceptance criteria, documentation deliverables, knowledge-transfer evidence, and executive reporting inputs.
Implement engineering quality controls to reduce rework, improve release confidence, and ensure that pilots, prototypes, and production capabilities follow appropriate quality and governance expectations.
Support 2027 planning by providing evidence-based recommendations for additional engineering, platform, MLOps, data engineering, QA, PMO, or product-pod capacity.
Manages the Software Engineering and AI teams in day-to-day performance of their responsibilities.
Ensures that projects, department milestones, and goals are met in accordance with the department and business strategies.
Conducts performance reviews, issues disciplinary action where required, drives the development of software engineers, hires new team members when applicable.
Build a culture of accountability, engineering rigor, collaboration, customer focus, continuous improvement, and measurable delivery outcomes.
Provide management reporting on delivery progress, release readiness, blocker aging, product adoption, engineering quality, capacity constraints, vendor risks, and value realization.