Y Combinator AI Engineer
Posted Updated 15
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Summary
An AI Engineer at Tractian develops and optimizes large language model (LLM) applications and backend systems, collaborating with cross-functional teams to ensure project success and efficient deployment.
Engineering at Tractian
The Engineering team at Tractian is at the forefront of developing cutting-edge infrastructure, technologies, and products to harness the power of IoT data. Our team of talented engineers collaborates to build robust systems, innovative solutions, and scalable platforms that drive Tractian's success. We are instrumental in shaping the company's decision-making process, optimizing operational efficiency, and delivering exceptional experiences to our customers.
What will you do
As an AI Engineer, you will play a key role within the Software Team, collaborating closely with developers, engineers, and product teams to support project organization, scheduling, and successful deployments. You will help ensure smooth coordination across various departments to achieve objectives and complete assigned tasks effectively. This role involves engaging with multiple moving parts and offers the opportunity to contribute across diverse aspects of the Software Team's work. You will help streamline processes, enhance team efficiency, and directly contribute to the company's overall success.
Responsibilities
- Contribute to Projects: Support planning and execution of software projects to deliver on time and at the highest quality.
- Collaborate with the Team: Work closely with developers, sharing knowledge and fostering high performance.
- Support Technical Decisions: Contribute to decisions on backend architecture, scalability, and infrastructure.
- Collaborate Cross-Functionally: Work with software, product, engineering, and other departments for seamless execution.
- Optimize Processes: Streamline workflows, solve technical challenges, and improve productivity.
- Support Deployments: Help ensure smooth, efficient deployments and system performance.
Requirements
- 5+ years in backend development specializing in scalable system design, API architecture (DDD), and microservices (gRPC, REST), with expertise in databases (Postgres, MongoDB, Redis, Clickhouse) and cloud infrastructure (AWS).
- Proficient in TypeScript and Golang, with extensive testing experience (unit, end-to-end, and load testing using Cypress, Playwright, k6).
- Skilled in containerization (Docker, Kubernetes) and DevOps practices, including CI/CD pipelines, infrastructure as code (IaC), and system monitoring (Datadog, Grafana).
- Experienced in developing and optimizing LLM applications, including Retrieval-Augmented Generation (RAG) and GPT-based solutions, with strong knowledge of deployment patterns, prompt engineering, and API integration (OpenAI, Anthropic, Gemini).
- Proficient in ML frameworks (PyTorch), optimization techniques (quantization, model distillation), and vector databases (pgvector, Weaviate, Pinecone).
- Experienced with LLM inference stacks (TensorRT-LLM, VLLM, llama.cpp) and developing RAG systems.
- Strong problem-solving and analytical skills, with excellent communication to foster cross-functional collaboration and stakeholder alignment.
- Strong track record of contributing to full development lifecycles, using issue tracking tools (Linear), and delivering complex backend systems on time.
- Experience in startups or high-growth environments, with deep expertise in system optimization tools and processes.
- Bachelor's degree in Computer Science or Engineering.
Compensation & Benefits
- Competitive Compensation
- Premium Medical, Dental, and Vision Coverage
- Paid Time Off (PTO): 15 Days
- 401(k) Retirement Plan
- Wellhub Membership - Access a wide range of gyms and training programs.
- Long-Term Benefit - After four years of service, earn a fully funded trip anywhere in the world.
Skills
- AI
- Anthropic
- API
- AWS
- CI/CD
- ClickHouse
- Cloud
- Containerization
- Cypress
- Datadog
- DevOps
- Docker
- Go
- Grafana
- gRPC
- Infrastructure as Code
- k6
- Kubernetes
- LLM
- Machine Learning
- Microservices
- MongoDB
- OpenAI
- pgvector
- Pinecone
- Playwright
- PostgreSQL
- Prompt Engineering
- PyTorch
- Quantization
- RAG
- Redis
- TensorRT
- TypeScript
- Vector Databases
- vLLM
- Weaviate