
Software Engineering Project Manager (AI Programs)
Intellisoft Technologies · California, TX · Hybrid
Weak hiring record · median 264 days open
All reasons
- Open 48 days
In its favour
- Still listed on the employer's own board
Job Description – Software Engineering Project Manager (AI Programs)
Job Title
Software Engineering Project Manager – AI Initiatives
Location
Houston, TX or Austin, TX (Hybrid- 3 days from office)
Employment Type
Full-Time / Contract
Position Summary
Client is seeking a Software Engineering Project Manager to lead the execution of strategic AI-driven software initiatives. This role requires an experienced technical project manager who can coordinate cross-functional engineering teams building AI-enabled products and platforms. The ideal candidate combines strong software engineering project management expertise with an understanding of modern AI/ML technologies, cloud platforms, Agile methodologies, and enterprise software development.
The Project Manager will collaborate closely with Engineering, Product Management, Data Science, AI/ML Engineers, QA, UX, DevOps, and executive stakeholders to ensure successful delivery of innovative AI solutions.
Key Responsibilities
- Lead end-to-end delivery of AI software development projects from planning through production deployment.
- Manage project scope, timelines, milestones, budgets, dependencies, and risk mitigation.
- Coordinate engineering teams including Software Engineers, AI/ML Engineers, Data Scientists, QA, DevOps, and Product Managers.
- Facilitate Agile ceremonies including Sprint Planning, Daily Standups, Backlog Grooming, Sprint Reviews, and Retrospectives.
- Track project health using Jira dashboards, KPIs, burndown charts, and executive status reporting.
- Work with Product Owners to prioritize AI product roadmaps and feature releases.
- Coordinate deployment activities across development, testing, staging, and production environments.
- Drive cross-functional communication across multiple business units and executive leadership.
- Identify technical and delivery risks and proactively develop mitigation strategies.
- Support resource planning and capacity management across engineering teams.
- Ensure software development follows SDLC best practices, coding standards, security policies, and quality processes.
- Manage vendor and third-party technology partners when applicable.
- Coordinate release management and post-production support activities.
- Prepare executive presentations, project documentation, RAID logs, and status reports.
Required Qualifications
- Bachelor's degree in Computer Science, Software Engineering, Information Systems, or related discipline.
- 8+ years of Software Engineering Project Management experience.
- Experience managing enterprise software development programs.
- Proven experience delivering AI, Machine Learning, Data Analytics, or Generative AI initiatives.
- Strong understanding of Agile, Scrum, Kanban, and SDLC methodologies.
- Experience working with geographically distributed engineering teams.
- Excellent stakeholder management and executive communication skills.
- Strong problem-solving and organizational abilities.
Preferred Certifications
- PMP
- Certified Scrum Master (CSM)
- PMI-ACP
- SAFe Agilist
- Microsoft Azure AI Fundamentals (AI-900)
- AWS Certified Cloud Practitioner or Solutions Architect
Desired Experience
- Enterprise AI product development
- AI-powered automation initiatives
- Intelligent document processing
- Conversational AI or chatbots
- Predictive analytics platforms
- Recommendation systems
Ideal Candidate Profile
The ideal candidate has 8–15 years of experience managing enterprise software engineering projects, with recent exposure to AI/Generative AI initiatives. They should be comfortable leading cross-functional engineering teams, managing Agile delivery, coordinating cloud-based software development, and communicating effectively with executive stakeholders. Experience delivering projects involving LLMs, AI Agents, RAG architectures, cloud platforms, and modern DevOps practices will be highly valued, even if they have not been hands-on in AI development.
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