Responsibilities:
Designing and writing code that is critical for business growth
Mastering scalability and enterprise-grade SAAS product implementation
Sense of ownership – leading design for new products and initiatives as well as integrating with currently implemented best-practices
Building and owning production-grade ETL/ELT pipelines that power analytics, ML training, and real-time AI systems
Designing data architectures that support agentic systems, including:
Embeddings and vector-based retrieval
RAG pipelines
Feedback loops and continuous improvement
Review your peer's design and code
Work closely with product managers, peer engineers, and business stakeholders
5+ years of hands-on experience as Software Engineer with Strong Python skills (TypeScript / Node.js is a plus)
Hands on experience in managing major clouds vendors infrastructure (AWS, GCP, Azure)
Proficiency with SQL, modeling and working with relational and non relational databases, and pushing them past their limits
Hands on experience in designing and implementing ML-aware data pipelines (Spark, Airflow), distributed systems and restful APIs
Experience or strong interest in LLMs and agentic systems, including:
Agentic workflows (LangChain, LangGraph)
RAG patterns, Vector databases and embeddings
Evaluating and monitoring AI-driven systems (Langfuse LangSmith)
Familiarity with ML & AI tooling, such as:
Feature stores, training pipelines, or model-serving data flows
ML platforms (MLflow, SageMaker, Vertex, etc.)
Experience with CI/CD, Docker, and Kubernetes
The ability to lead new features from design to implementation, taking into consideration topics such as performance, scalability, and impact on the greater system
Comfortable operating in a fast-moving startup with high ownership and low process
Enjoy communicating and collaborating, sharing your ideas and being open to honest feedback

















