10 or more years of engineering leadership experience, including hiring, org design, and developing engineering talent while scaling multi team organizations.
Deep hands on experience architecting and delivering AI and ML systems, including LLM based applications, RAG architectures, and agentic AI patterns.
Advanced Python skills, with the ability to engage directly in architecture review and hands on technical problem solving.
Experience with Model Context Protocol or comparable interoperability and integration frameworks for AI systems.
Strong background in API design, microservices, and modern cloud native architectures such as Azure, AWS, or GCP.
Experience improving engineering delivery velocity through tooling, process, and AI assisted development practices.
Working familiarity with product lifecycle management practices and the ability to partner effectively with product management without owning the product roadmap directly.
Strong understanding of data pipelines, data platforms, and the data foundations required for AI at scale.
Solid grounding in data science concepts and principles, including statistical reasoning, model evaluation, and data quality practices.
Experience establishing AI governance, model risk management, and responsible AI practices.
Strong technical judgment on high scalability, high performance system design.
Proven ability to operate and influence at the executive level across Engineering, Product, and business stakeholders.
Experience owning infrastructure and vendor cost accountability, including cost monitoring, unit economics, and ROI measurement for technology investments.
Experience establishing security practices for AI and agentic systems, including threat modeling and identity and access patterns for automated systems.
Nice to have
Background leading AI engineering in a SaaS or enterprise software environment.
Experience leading globally distributed engineering teams across multiple regions.
A track record of leading engineering organizations through significant technical or organizational transformation.
Comfortable running vendor evaluations and build versus buy assessments for AI platforms and tooling.
Has integrated AI capabilities into acquired products or teams following an acquisition.
Full description
Director, AI Engineering
MRI Software is seeking a Director of AI Engineering to lead the architecture and delivery of AI capabilities across MRI's platform and product portfolio. This is a technical leadership role, owning how AI gets built, integrated, and operated at scale, and building the engineering organization behind it. The Director will own the shared AI platform and its underlying data and knowledge foundation, drive AIOps practices and economic accountability for AI infrastructure, and champion modern AI engineering practices including agentic systems, Model Context Protocol and related interoperability standards, AI assisted development, and enterprise agent ecosystem design. The role establishes reusable architecture patterns and self-service platform capabilities across MRI's business units, partners closely with product, IT, data, and security leadership, and drives adoption of AI-native engineering practices within the organization. The Director also engages directly with customers and executive leadership on AI trust, adoption, and business impact.
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Key Responsibilities
Define and drive MRI's AI engineering roadmap, including build versus buy decisions, platform architecture, and technology direction.
Lead and scale the AI engineering organization responsible for model integration, RAG systems, agent orchestration, and AI platform services, including hiring, org design, and coaching engineering leaders and architects.
Own the shared AI platform, including prompt management, evaluation frameworks, vector databases, model gateway and routing services, and agent registries.
Champion adoption of Model Context Protocol and other emerging interoperability standards to connect AI capabilities across MRI's product ecosystem.
Define MRI's enterprise agent ecosystem approach, including agent interoperability, shared memory and context management, cross-product orchestration, and reusable agent capabilities across the portfolio.
Architect and scale agentic AI ecosystems that operate across multiple products, data sources, and internal systems.
Define AI reference architectures and reusable patterns for the AI engineering organization, driving standardization over product level fragmentation.
Partner with product leadership to translate AI roadmap priorities into engineering execution and sequencing.
Establish engineering practices, tooling, and governance that increase delivery velocity for AI powered features across the organization.
Drive AI assisted development practices, including AI assisted coding and workflow tooling, to improve engineering team productivity.
Own model lifecycle management, from evaluation and selection through deployment, monitoring, and retirement.
Select the best fit models and AI technologies for a given use case, balancing cost, quality, and scale tradeoffs.
Director, Product Development at MRI Software (Bangalore, India Office) — aijobsearch
Establish AIOps and LLMOps practices, including observability and telemetry, hallucination detection, and continuous evaluation and benchmarking of models and agents.
Own AI infrastructure and model consumption costs, establishing unit economics and ROI measurement for AI features and driving FinOps discipline across the AI platform.
Set standards for API design and integration patterns that support AI feature delivery across MRI's platforms.
Own the knowledge architecture underlying AI systems, including semantic layers, metadata and context management, data governance for AI, and knowledge graph design.
Partner with data engineering and platform teams to ensure the data foundation supports AI initiatives at scale.
Evaluate and pilot emerging AI technologies, translating industry trends into practical initiatives for MRI.
Establish governance and responsible AI practices for model usage, data handling, and agent behavior, including AI and agent security, threat modeling, prompt injection defense, data leakage prevention, and identity and authorization patterns for agents.
Qualifications
10 or more years of engineering leadership experience, including hiring, org design, and developing engineering talent while scaling multi team organizations.
Deep hands on experience architecting and delivering AI and ML systems, including LLM based applications, RAG architectures, and agentic AI patterns.
Advanced Python skills, with the ability to engage directly in architecture review and hands on technical problem solving.
Experience with Model Context Protocol or comparable interoperability and integration frameworks for AI systems.
Strong background in API design, microservices, and modern cloud native architectures such as Azure, AWS, or GCP.
Experience improving engineering delivery velocity through tooling, process, and AI assisted development practices.
Working familiarity with product lifecycle management practices and the ability to partner effectively with product management without owning the product roadmap directly.
Strong understanding of data pipelines, data platforms, and the data foundations required for AI at scale.
Solid grounding in data science concepts and principles, including statistical reasoning, model evaluation, and data quality practices.
Experience establishing AI governance, model risk management, and responsible AI practices.
Strong technical judgment on high scalability, high performance system design.
Proven ability to operate and influence at the executive level across Engineering, Product, and business stakeholders.
Experience owning infrastructure and vendor cost accountability, including cost monitoring, unit economics, and ROI measurement for technology investments.
Experience establishing security practices for AI and agentic systems, including threat modeling and identity and access patterns for automated systems.
Education
Bachelor's degree in Computer Science, Engineering, or a related technical field required.
Technical graduate degree preferred.
Preferred Experience
Background leading AI engineering in a SaaS or enterprise software environment.
Experience leading globally distributed engineering teams across multiple regions.
A track record of leading engineering organizations through significant technical or organizational transformation.
Comfortable running vendor evaluations and build versus buy assessments for AI platforms and tooling.
Has integrated AI capabilities into acquired products or teams following an acquisition.
Benefits:
Hybrid working arrangements
6x Flexi Holidays: knock 2.5 hours off your day on any day.
Medical insurance coverage for extended family members.
Engaging, fun & inclusive culture: check out the MRI Software APAC Insta feed and stories!
About Us
From the day we opened our doors, MRI Software has built flexible, game-changing real estate software that powers thriving communities and helps make the world a better place to live, work and play. Fulfilling that mission is only possible because of one thing: exceptional people. People like you!
Our people-first approach to PropTech is defining a new industry standard for client experiences that, quite frankly, can’t be duplicated. Experiences that deliver real value every day. And we know those experiences begin with our people.
We believe MRI is more than just a workplace; it’s a connected community of people who truly feel they belong. Whether we’re investing in employee resource groups or providing tailored resources for each person to reach their full potential, we’re passionate about creating a work environment that makes you excited to show up every single day.
At MRI, one of our core values is to strive to amaze. From the intelligent solutions we create to the culture we cultivate, that’s our goal every day. Because that’s what industry leaders do. Whether you’re joining as a new Pride member or rejoining us after a short time away, your talent is vital to us, our partners and our clients.
Amazing growth requires amazing employees. Are you up to the challenge?
We know confidence gap and imposter syndrome can get in the way of meeting remarkable candidates, so please don’t hesitate to apply. We’d love to hear from you!
MRI is proud to be an inclusive employer. We welcome and celebrate diversity across all backgrounds, including ethnicity, religion, sexual orientation, gender identity, disability, age, military, veteran status and more.
We believe that Belonging is a direct result of Diversity, Equity, and Inclusion. Those values are woven into the fabric of who we are and are foundational to our continued success. Come and see for yourself!