Senior Software Engineer

• 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.

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., * 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.

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.