| Company | Replika |
| Job title | Senior AI Engineer |
| Job location | Remote |
| Type | Full Time |
Responsibilities:
- Build, manage, and optimize backend systems and APIs supporting AI/ML workloads.
- Support and maintain robust data and ML pipelines, ensuring scalability and reliability.
- Develop FastAPI-based microservices leveraging Python async patterns.
- Manage state and flow tracking using Redis and MongoDB, optimizing performance and persistence layers.
- Integrate with LLMs (LLaMA, OpenAI, Anthropic) and support vector database operations (e.g., Pinecone).
- Implement and maintain Docker-based containerized environments for both development and production.
- Design and monitor event-driven systems using Kafka.
- Implement structured logging (Structlog/Logfire) and observability solutions (e.g., Datadog).
- Collaborate with the DevOps team on CI/CD pipelines using GitHub Actions.
- Contribute to Quadrant integration for deployment and operational alignment.
- (Optional) Provide support for Scala-based components, if applicable.
Requirements & Skills:
- Minimum 5+ years of experience with Python development
- Experience with Redis (especially asyncio clients) for state tracking and flow control.
- Strong understanding of MongoDB query patterns and schema design.
- Experience working with Large Language Models, including LLaMA (3.x preferred).
- Hands-on with LLM APIs such as OpenAI, Anthropic, etc.
- Experience with vector databases like Pinecone, understanding semantic search, and embeddings.
- Proficient with Docker and Docker Compose
- Experience in event-driven systems with Kafka (producers/consumers).
- Strong grasp of CI/CD using GitHub Actions.
- Familiarity with the Quadrant for deployment orchestration.
- Comfortable with logging/monitoring tools such as Datadog.
- Proven experience collaborating with cross-functional stakeholders
- Experience with systems serving at scale (at least 500k+ users)
- Startup mindset: proactive, adaptive, and comfortable navigating ambiguity
Nice to Have
- FastAPI for building async APIs and microservices.
- Familiarity with Scala or willingness to learn it.
- Experience with Kubernetes or other orchestration tools.
- Prior work in AI/ML-focused product teams or research environments.
- Experience in leadership roles such as Team Lead, Engineering Manager, or Staff Engineer
