AI Engineer
Tasks
- Build prompt engineering and prompt evaluation pipelines
- Collaborate on architecture code review and technical direction
- Convert prototypes to production services
- Design build and maintain LLM powered features and pipelines
- Develop and improve agentic systems and multi agent workflows
- Implement structured output generation and validation
- Integrate MCP servers and tooling
- Monitor and manage LLM cost latency and reliability
- Write production backend Python services for LLM APIs
Perks/Benefits
- Bonuses for special events
- Catered lunches
- Corporate events and workshops
- Health insurance
- Hybrid work model
- Mental health services
- Onsite gym
- Training and development
- Tuition reimbursement
Skills/Tech-stack
Agent systems | Anthropic API | Concurrency | Cost Optimization | Docker | Git | LLM Cost Optimization | LLM Latency Optimization | Language Models | Large Language Models | Latency optimization | Model Context Protocol | Multi-Agent | Multi-Agent Systems | OpenAI API | Prompt engineering | Prompt evaluation | Python | REST APIs | Reliability Engineering | SQL | Structured outputs | XAI API
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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