// ABOUT_US
Who we are
ProductSquads was founded with a bold mission: to engineer capital efficiency through autonomous AI agents, exceptional engineering, and real-time decision intelligence.
We're building an AI-native platform that redefines how software teams deliver value — whether through code written by humans, agents, or both. Our stack combines agentic AI systems, ML pipelines, and high-performance engineering workflows.
This is your chance to build not just models, but systems that think, decide, and act — AI fabric tools, domain-intelligent agents, and real-time decision systems that power the next generation of product delivery.
// THE_ROLE
What you'll build
The AI Delivery Manager is a next-generation leadership role responsible for transforming how engineering teams deliver software using AI-powered systems, automation, and intelligent workflows.
The AI Delivery Manager bridges Product and Engineering, designs AI-enabled delivery frameworks, and ensures teams deliver faster, more predictably, and with higher quality.
This role plays a central part in building AI-powered delivery ecosystems, integrating MCP frameworks, AI agents, and automated governance into the software delivery lifecycle.
// RESPONSIBILITIES
Your scope
Bridge Product Requirements with Engineering Execution
- Translate product requirements into clear, executable engineering deliverables.
- Evaluate technical feasibility and architectural implications of product requests.
- Ensure requirements are testable, traceable, and automation-ready.
- Maintain traceability from requirements → development → testing → deployment.
Build AI-Enabled Delivery Systems
- Design and deploy AI-powered delivery frameworks.
- Implement Model Context Protocol (MCP) based systems.
- Architect and orchestrate multi-agent AI workflows.
- Integrate AI governance, guardrails, and validation into CI/CD pipelines.
- Build reusable AI delivery accelerators and automation frameworks.
Technical Evaluation & Architecture Review
- Evaluate system architecture and engineering decisions.
- Assess AI frameworks, scalability risks, and vendor solutions.
- Review LLM implementations, vector databases, embeddings, and AI pipelines.
- Ensure governance, reliability, and security in AI systems.
Delivery Ownership & Decision Making
- Own delivery outcomes across programs.
- Use AI tools, metrics, and data insights to make delivery decisions.
- Identify delivery risks early and resolve dependencies proactively.
- Improve delivery predictability, lead time, and release quality.
Program & Stakeholder Leadership
- Drive alignment between Product, Engineering, and Leadership.
- Provide technical clarity to senior stakeholders.
- Maintain visibility into delivery health and program performance.
- Ensure release readiness and governance compliance.
// REQUIREMENTS
What you'll bring
Technical & Engineering Background
- 4+ years of hands-on technical experience in roles such as Software Engineer, Tech Lead, DevOps Engineer, Platform Engineer, ML Engineer, or Solutions Architect.
- Strong programming experience in Python, JavaScript, or similar languages.
- Experience designing and managing CI/CD pipelines.
- Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
- Solid understanding of DevOps and MLOps practices.
AI & Agent Systems Experience
- Experience building AI agent workflows and intelligent automation systems.
- Hands-on exposure to frameworks such as LangChain, AutoGen, CrewAI, or similar agent orchestration tools.
- Strong understanding of:
- Large Language Models (LLMs)
- Embeddings and vector databases
- Retrieval-Augmented Generation (RAG) systems
- AI model evaluation and guardrails
Delivery & Leadership
- Experience leading complex engineering or technical delivery initiatives.
- Strong understanding of Agile and flow-based delivery methodologies.
- Ability to drive delivery improvements using data, metrics, and automation.
- Experience working with cross-functional teams and managing program-level execution.
Communication & Decision-Making
- Strong ability to evaluate technical solutions, architecture, and implementation approaches.
- Excellent stakeholder communication and collaboration skills.
- Systems-thinking mindset with a focus on building AI-enabled delivery ecosystems.
// BENEFITS
What we offer
- Monday to Friday workweek with flexible working hours
- Paid time off and holidays
- Medical insurance
- Professional development and training budget
- A dynamic, collaborative, ship-fast environment