Messaging Product Owner responsible for enterprise messaging platforms at KPMG. Leading engineering and product ownership for Exchange Online, Proofpoint, and M365 collaboration tools.
About the role
- Staff Engineer leading design and development of AI applications at Tinder. Focused on generative AI and LLMs to build applied systems for productivity enhancement.
Responsibilities
- Lead the development of AI applications that integrate LLMs with APIs, databases, and enterprise systems.
- Oversee the design and optimization of AI agent & pipelines to enhance factuality.
- Build scalable agentic workflows and orchestration systems for enterprise use cases.
- Own the architecture and design of applied AI systems (bots, RAG, agents, integrations, MCP servers).
- Define patterns, frameworks, and reusable components to accelerate AI solution delivery across teams.
- Drive evaluation and guardrail frameworks for ensuring AI reliability, safety, and performance.
- Partner with product managers and stakeholders to translate ambiguous business needs into technical solutions.
- Mentor engineers, review designs/code, and guide teams in applied AI best practices.
- Collaborate with security, compliance, and data teams to ensure responsible AI adoption.
- Stay ahead of emerging LLM frameworks, orchestration tools, and AI agents.
- Identify opportunities for new AI-powered capabilities within existing systems.
- Contribute to long-term AI roadmap and platform strategy.
Requirements
- Strong experience in Python, TypeScript/JavaScript, and distributed systems.
- Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.), orchestration frameworks (LangChain, LlamaIndex, CrewAI, LangGraph), and vector databases (Elasticsearch, Pinecone, etc.).
- Proven track record of building production-grade AI applications (bots, agents, RAG systems).
- 8+ years of software engineering experience with 2+ in applied AI/ML.
- Prior experience as a tech lead or staff-level engineer, influencing technical direction beyond a single team.
- Strong ability to communicate AI concepts to both technical and non-technical stakeholders.
- Exceptional ability to abstract problems into AI-powered workflows.
- Skilled at balancing rapid prototyping with building for scale and reliability.
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