Engineering Manager

Engineering Manager
Accelerate Performance.
About CAI Software
CAI Software builds purpose-built solutions that help manufacturers, processors, and distributors accelerate performance. Our mission is to enable manufacturers to transform performance through a connected, AI-assisted ecosystem that delivers visibility, control, and continuous improvement. We bring the deep operational expertise and enterprise infrastructure to be a true long-term performance partner.
With 6,200+ active customers worldwide and a market-leading position in every vertical we serve, CAI combines 45+ years of industry expertise with modern AI-driven execution - helping businesses move faster, operate smarter, and perform at their peak. We work across 15+ industries and 10+ countries, guided by three values built into our name: Candor, Accountability, and Impact.
CAI Business Units and the Markets We Serve
CAI Software is organized into three business units: Graphic Communications, Process Manufacturing, and Discrete Manufacturing - aligned to the industries we serve. This structure keeps our teams close to customer needs while operating with the scale and support of a global software company.
CAI India
CAI India is a strategic investment in the company’s future. Our Bangalore Center of Excellence is a place of ownership, expertise, and accountability. Teams in India work on global products end to end, contribute to key decisions, and influence how CAI evolves as a business. This is not a support-led model, but rather a center designed to lead through knowledge, responsibility, and trust.
Key Responsibilities
Own end-to-end delivery for the EDI Products engineering team, ensuring commitments made to Product Management and Product Owners are met on time and with quality.
Partner with Product Managers and Product Owners to translate roadmap items, epics, and backlog priorities into a well-sequenced, achievable engineering plan.
Champion AI-led development practices across the team — embedding AI-assisted coding, testing, and documentation tools into day-to-day engineering workflows to improve velocity and code quality.
Manage the team’s use of Azure DevOps (ADO) and ADO-Git for work item tracking, sprint/iteration planning, branching strategy, pull requests, and release management.
Collaborate with Product Management in Aha! to keep roadmap, initiatives, and feature-level plans aligned with engineering capacity and delivery status.
Ensure engineering standards, designs, and decisions are documented and kept current in Confluence for team and cross-functional visibility.
Run agile ceremonies (sprint planning, standups, retrospectives, backlog refinement) and drive continuous improvement in team process and delivery predictability.
Coach, mentor, and develop engineers; conduct performance reviews, set growth goals, and support career development within the team.
Manage team capacity, staffing needs, and hiring in partnership with the VP of Engineering.
Identify technical risks, dependencies, and quality issues early, and drive mitigation plans in collaboration with engineering and product stakeholders.
Report delivery status, risks, and metrics to the VP of Engineering and other stakeholders on a regular cadence.
Support and enforce secure, compliant engineering practices appropriate to EDI and manufacturing data integration workloads.
AI-Led Development
This role requires active leadership in adopting AI-assisted engineering practices as a core part of how the team builds and ships software, including:
Guiding engineers in the effective use of AI coding assistants for implementation, code review, refactoring, and test generation.
Establishing team norms and guardrails for responsible, secure use of AI tools with proprietary and customer-related code and data.
Measuring and reporting the impact of AI-led development on delivery speed and quality, and continuously refining the approach.
Staying current on AI-assisted software development practices and evaluating new tools/approaches for team adoption.
Tools & Platforms
Azure DevOps (ADO) and ADO-Git
Aha! (Product roadmap and planning alignment)
Confluence (Engineering documentation and knowledge sharing)
AI-assisted development tooling as adopted by the organization
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
10+ years of software engineering experience, including 2+ years in an engineering management or team lead role.
Proven experience managing software delivery using Azure DevOps (ADO) work items, boards, and ADO-Git repositories/pull requests.
Experience partnering directly with Product Managers and/or Product Owners to plan and prioritize engineering work.
Hands-on familiarity with AI-assisted development tools and a demonstrated interest in applying them to improve team output.
Strong people-leadership skills: coaching, performance management, and building a high-trust, high-accountability engineering culture.
Excellent written and verbal communication skills, with the ability to translate technical topics for non-technical stakeholders.
Preferred Qualifications
Experience with EDI, B2B integration, or manufacturing/supply-chain software domains.
Experience modernizing legacy systems or leading teams through technology migrations.
Background in .NET, middleware/integration platforms, or ISAM/relational data systems.
What Success Looks Like
Predictable, high-quality delivery against roadmap commitments made with Product Management.
Measurable adoption and impact of AI-led development practices within the team.
A well-documented, well-governed engineering process in ADO, Aha!, and Confluence that stakeholders trust.
An engaged, growing engineering team with clear goals and strong retention.
Why Join CAI
At CAI, we are building something that matters. With 6,200+ customers across 15+ industries and active investment in AI-driven performance tools, we are positioned to define what the next generation of manufacturing software looks like — and we are building the team to lead that work.
Our four pillars define how we deliver for customers — and how we work:
Built to Fit - Fits how your business runs so performance comes standard
Built to Expedite - Speeds time to performance without heavy lifts or delays.
Built to Deliver - AI turns action and insights into measurable performance.
Built to Scale - Sustains and scales performance without disruption.

Work arrangement
No