We are looking for a Senior Software Engineer – Lakehouse & Applied AI with strong hands‑on experience in Databricks, PySpark, Python, cloud infrastructure, and GenAI/LLM technologies.
The ideal candidate will combine data engineering and software engineering expertise with experience building production-grade AI/LLM solutions, cloud platforms, infrastructure‑as‑code, and containerized workloads.
This role involves owning solutions end‑to‑end, from discovery and rapid prototyping through production deployment, while working directly with stakeholders in a forward‑deployed environment.
Key Responsibilities
- Design and deliver end‑to‑end lakehouse and applied-AI solutions from prototype through production.
- Build scalable data platforms using Databricks, PySpark, Delta Lake, and Azure.
- Develop agentic AI workflows and tool‑using AI agents for software and infrastructure automation.
- Build AI solutions using LLMs, embeddings, RAG, and MCP or similar tool‑serving frameworks.
- Develop reusable multi‑tenant CI/CD and deployment frameworks.
- Build and deploy local/edge LLM and embedding‑serving environments.
- Develop Python‑based REST APIs and microservices using FastAPI, Flask, or similar frameworks.
- Deploy and orchestrate production workloads using Docker, Kubernetes, ECS/Fargate, and Airflow.
- Manage cloud infrastructure using Terraform and Terragrunt across Azure and AWS.
- Work with services including Azure Databricks, ADLS Gen2, Key Vault, AWS ECS, S3, RDS, SQS, and SSM.
- Develop AI evaluation and testing frameworks covering regression detection, retrieval quality, task completion, and safe rollback.
- Implement monitoring and observability using tools such as Prometheus and Grafana.
- Work directly with customers and stakeholders to translate ambiguous requirements into production‑ready technical solutions.
Required Qualifications
- 6+ years of experience in software/data engineering.
- Strong hands‑on experience with Databricks, PySpark, Delta Lake, and Python.
- Experience with Medallion Architecture, Auto Loader, Unity Catalog, and Databricks Asset Bundles.
- Hands‑on experience with GenAI, LLMs, AI agents, RAG, embeddings, or agentic workflows.
- Working knowledge of MCP or similar LLM tool‑serving frameworks.
- Strong experience with Terraform and Terragrunt.
- Experience across Azure and/or AWS cloud environments.
- Hands‑on experience with Docker, Kubernetes, ECS/Fargate, and CI/CD.
- Strong Python development skills with FastAPI, Flask, REST APIs, and microservices.
- Experience with Airflow or similar workflow orchestration tools.
- Knowledge of Prometheus, Grafana, or similar observability platforms.
- Strong problem‑solving skills with the ability to own solutions from prototype to production.
- Comfortable working in a customer‑facing, forward‑deployed engineering environment.
Preferred Qualifications
- Experience with local/on‑premises LLM deployment using Ollama, Llama, Hugging Face, or similar technologies.
- Experience working with Snowflake alongside Databricks.
- Experience building multi‑tenant data or AI platforms.
- Telecommunications experience involving 3G/4G‑LTE OSS/BSS, network management, backhaul, or 5G.
- Experience with AI‑assisted software engineering and autonomous/agentic development workflows.
- Experience optimizing production systems for latency, reliability, scalability, and cost.
ABOUT BRICKRED SYSTEMS
BrickRed Systems is a global leader in next‑generation technology consulting and workforce solutions, specializing in delivering high‑quality talent across digital, engineering, marketing, analytics, finance, operations, and business transformation domains. With a strong emphasis on innovation, scalability, and client success, BrickRed Systems helps organizations solve complex business challenges by providing skilled professionals across strategy, technology, creative, and operational functions. BrickRed fosters a culture of continuous learning, collaboration, and excellence, enabling professionals to contribute to high‑impact global initiatives while advancing their careers.