Prosum is seeking a Manager of Generative AI Engineering to lead and build production-grade GenAI systems in a fast-growing enterprise environment. This role involves a blend of hands-on engineering and people leadership, where the manager will lead a team of engineers while also being deeply involved in system design and implementation.
Responsibilities:
- Lead, mentor, and develop engineering teams focused on generative AI solutions
- Set clear expectations, coach performance, and foster a culture of ownership and continuous improvement
- Translate business and product requests into well-scoped engineering initiatives
- Hire, onboard, and grow high-performing engineers
- Run delivery cycles including sprint planning, backlog grooming, and dependency management
- Own operational outcomes for AI systems (reliability, latency, cost, scalability)
- Communicate progress, risks, and technical tradeoffs to technical and non-technical stakeholders
- Design and build production-grade generative AI systems
- Develop LLM-powered features including multi-step RAG pipelines and agentic workflows
- Define reusable patterns for prompt management, workflow versioning, structured outputs, and rollback strategies
- Build and maintain automated evaluation pipelines for LLM outputs (testing and regression)
- Implement AI guardrails, human-in-the-loop workflows, and schema-based validation
- Secure AI systems against data leakage, prompt injection, and unauthorized access
- Integrate AI services with enterprise data sources, internal APIs, and cloud platforms
- Continuously evaluate new models and tools, improving systems incrementally
Requirements:
- 7–15 years of experience with a strong foundation in software engineering
- Proven experience shipping generative AI or LLM-based systems to production
- Hands-on experience with: LLMs, prompt and workflow design
- RAG architectures or agent-based systems
- AI evaluation, testing, and quality validation
- Experience leading or mentoring engineers (manager, tech lead, or senior IC ready to step up)
- Strong understanding of operating production systems (performance, reliability, cost)
- Ability to translate ambiguous requirements into actionable engineering work
- Experience working in enterprise or compliance-sensitive environments
- Bachelor's degree in Computer Science, Engineering, or equivalent experience
- Experience with ecommerce platforms, product data, PIM, ERP, or analytics systems
- Azure or Azure OpenAI experience
- Python frameworks such as FastAPI, asyncio, or Pydantic
- Experience with microservices, APIs, and containerized deployments (Docker)
- Familiarity with responsible AI principles and governance
- Exposure to modern frontend stacks (Node.js, Next.js, React)