Tech Stack
AzureCloudDockerGrafanaJavaScriptKubernetesNext.jsPostgresPythonPyTorchRabbitMQRealmShell ScriptingSplunkSQLTensorflowTypeScript
About the role
- Facilitate effective communication with client project stakeholders regarding project status and recommendations, using Kanban as a framework.
- Craft and maintain client code that is not just efficient but also performant, testable, scalable, secure, and of the highest quality.
- Actively participate in calls with clients (if needed).
- Promote client success across the team by collaborating with engineers, designers, and managers to understand user pain points, anticipate potential problems, and iterate on solutions that drive client success.
- Engage in Triage calls together with the customer team.
- Actively participate in the Engineering Practice community, mentoring others through Communities of Practice (CoPs) or on project teams and supporting the growth of technical capabilities.
- Independently drive project delivery within defined architecture, demonstrating autonomy and accountability in all stages from conceptualization to deployment.
Requirements
- A minimum of 5+ years of experience/expertise in the following areas specified below*:
- HTML, CSS, JavaScript, Typescript, NextJS
- Python, Fast API
- Postgres SQL
- RabbitMQ or Azure Service Bus
- Log aggregation systems such as Grafana Loki, Application Insights, Splunk, etc.
- Git/GitHub
- Experience with the following AI related skills and technologies:
- Collaborating with software engineers to embed AI in products
- Prompt Engineering
- Any of the following: Lang chain, Langgraph, Pytorch or TensorFlow
- Retrieval Augmented Generation with Qadrant, FAISS, Weaviate, or similar technologies
- Designing and implementing agentic AI workflows, including orchestration and tool integrations
- AI-enhanced development with Cursor, Copilot, Windsurf or similar tool Familiarity with fundamental concepts of LLMs, such as tokens, embeddings, hyperparameters, context windows.
- Experience in creating and implementing well-tested, scalable, and performant enterprise-level systems.
- Practice and initiative mentoring other engineers and decision-makers throughout the organization.
- Good understanding of SOLID principles.
- Proficiency in the English language.