Join us as a Manager 2 on our Generative AI Engineering team in India to lead building intelligent experiences and foundational Generative & Agentic AI capabilities across our platform.

What you'll achieve

As a Manager 2, you will lead a team focused on delivering Generative AI features, services, and infrastructure. Your team will build and maintain our AI capabilities including LLM integrations, agentic workflows, RAG pipelines, or AI powered product experiences that serve customers and internal users. You will collaborate with Product, UX, Data Science, and peer engineering teams to ship reliable, scalable AI solutions—from prompt engineering and model integration to production observability and user-facing features.

You will:

Lead Delivery of AI Features and Services

• Own end-to-end delivery of AI features, agent workflows, or platform components

• Partner with Product Managers, Designers, and Data Scientists to translate requirements into shipped capabilities

• Drive execution using agile practices with clear sprint goals, demos, and retrospectives
  

Build and Operate AI Systems

• Guide your team in building production AI systems such as:

  • LLM integrations and orchestrations

  • Prompt engineering and management

  • Agent implementations (tool calling, planning, memory)

  • RAG pipelines and vector search

  • Model evaluation and quality monitoring

  • Safety layers and guardrails
    

Manage Team Execution and Delivery

• Plan sprints, manage backlog priorities, and coordinate releases

• Remove blockers and create clarity for your team

• Track delivery using engineering and AI specific metrics (latency, cost, quality, adoption)

• Ensure reliable operation through monitoring, incident response, and continuous improvement
  

Coach and Develop Engineers

• Mentor engineers in Gen AI system design, LLM best practices, and production patterns

• Conduct 1:1s, provide feedback, and support career growth

• Foster a learning culture around emerging Gen AI technologies and techniques
  

Collaborate Across Teams

• Work closely with peer teams on shared Gen AI infrastructure and standards

• Communicate status, risks, and dependencies clearly to leadership and stakeholders

• Participate in technical design reviews and architectural discussions

Maintain Technical Excellence

• Stay hands-on with code reviews and architectural decisions

• Advocate for engineering best practices: testing, CI/CD, observability, documentation

• Balance innovation with stability and operational excellence

Own Quality and Reliability

• Ensure your team's deliverables meet production standards for high availability, performance, and safety

• Establish observability for model behavior, costs, and user experience

• Drive post-mortems and continuous improvement

Participate in Talent Development

• Interview and hire strong engineers with distributed systems and/or Gen AI experience

• Onboard new team members effectively

• Contribute to engineering culture and community building

Essential Requirements

• 2+ years of people management experience leading software engineering teams

• 5+ years of software development experience

• Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.) or frameworks (LangChain, LlamaIndex)

• Experience with agentic patterns: tool use, planning, retrieval, human-in-the-loop

• Experience building or operating RAG systems, vector databases, or semantic search

• Familiarity with LLMOps, model evaluation, and AI observability tools

• Experience with cloud platforms (AWS preferred) and modern DevOps practices

• SaaS or B2B product experience

• Experience shipping LLM-powered features or GenAI capabilities to production

• Solid understanding of LLM capabilities, prompt engineering, and common Gen AI patterns

• Strong foundation in building scalable, distributed backend systems

• Experience with agile delivery practices and cross-functional collaboration

• Strong communication skills and ability to articulate technical concepts to non-technical stakeholders

• Commitment to engineering excellence, quality, and operational responsibility

Nice to Have

• Experience managing teams working on AI/ML or data-intensive products

• Background in NLP, machine learning, or AI research

• Understanding of responsible AI, safety, and governance practices

• Experience with A/B testing and experimentation frameworks for AI features